Jobs ML / AI

This is a high-autonomy embedded delivery role where you orchestrate the intelligent agent systems you design yourself — owning the full loop from requirements to release, solo, on real client engagements.

A new team member will be in charge of:

• Own requirements shaping directly with the client, covering BA, PO, and UX work yourself.
• Design and write the project’s own AI agents and skills (Codex, Claude Code or comparable), not just prompt off-the-shelf tools.
• Choose and combine agents, skills, and models to fit the project’s business and technical goals, and keep evolving that setup as the project changes.
• Own the full SDLC and ship working software through that agent setup.
• Unblock large, messy backlogs fast.
• Make scope and trade-off calls that balance release dates against technical decisions, without waiting for an architect or PO.
• Represent the company’s AI delivery capability to the client, including under scrutiny.
• Stay ahead on new agentic tools and practices, and bring them back to the company.

Does this relate to you?

• 5+ years in software engineering or delivery, with ongoing client-facing responsibility.
• 1+ years of hands-on experience building custom agents and skills for real delivery work, with concrete examples of an agent setup you designed and what it shipped.
• A proven ability to cut scope to hit a release, and to explain why.
• Solid engineering fundamentals, enough to make and defend technical calls live and alone.
• A track record of delivering against hard deadlines with incomplete inputs.

Nice to have:

• A prior FDE or embedded-consultant role.
• An architecture background.
• Healthcare, fintech, or manufacturing domain experience.

Ready to try your hand? Send your CV without a doubt!

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv — you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Turn your curiosity for automation and AI into a technology career. 

We are looking for self-driven professionals from Assurance who have demonstrated a passion for improving the way work gets done through Python, automation, data analytics, Copilot, or Generative AI. Whether you have built scripts, automated repetitive tasks, experimented with AI tools, or simply enjoy exploring new technologies, this role offers an opportunity to transform that passion into a full-time technology career. 

As a Junior AI Engineer, you will learn how to design and develop scalable AI-powered solutions while combining your audit and business knowledge with modern engineering practices. Working alongside experienced AI engineers, you will gain hands-on experience with Python, Generative AI, cloud platforms, intelligent automation, and enterprise AI solutions. 

This is a career opportunity for professionals who want to evolve from being consumers of technology into creators of technology, helping shape how AI is used across PwC and for our clients. While previous AI engineering experience is not required, a genuine interest in technology, continuous learning, and hands-on experimentation is essential. 

Key Responsibilities 

AI Solution Development:

• Develop AI and automation solutions using Python. 
• Build and maintain integrations with LLM APIs and AI services.
• Support implementation of RAG-based applications.
• Assist in developing prompt engineering strategies and reusable AI components.
• Participate in testing, debugging, and improving AI solutions. 

Engineering Excellence:

• Write clean, maintainable, and well-documented code.
• Participate in code reviews and technical discussions.
• Create and maintain REST APIs and backend services.
• Support CI/CD pipelines and deployment activities.
• Follow secure coding and software engineering best practices. 

Data & AI Operations:

• Prepare and process structured and unstructured data.
• Assist with document processing, OCR, chunking, and embedding pipelines.
• Work with SQL and vector databases.
• Monitor AI solution performance and troubleshoot production issues. 

Learning & Innovation: 

• Continuously learn emerging AI technologies and frameworks.
• Contribute to internal proof-of-concepts and AI adoption initiatives.
• Share knowledge with the broader AI engineering community. 

Required Qualifications 

Technical Skills: 

• 1–3 years of experience in software development or automation.
• Good Python programming skills.
• Understanding of object-oriented programming and software engineering principles.
• Experience working with APIs and JSON data structures.
• Basic knowledge of Git and version control workflows.
• Understanding of relational databases and SQL.
• Familiariaty with cloud concepts (Azure preferred).
• Interest in Artificial Intelligence and Generative AI technologies. 

AI Knowledge:

• Experience using AI IDEs (Cursor/Copilot/Claude/and so on) during daily work.
• Basic understanding of:  Large Language Models (LLMs), Prompt Engineering, Embeddings, RAG concepts, Vector search fundamentals.

Nice-to-Have Skills

• LangChain, LangGraph, CrewAI, Semantic Kernel 
• Azure AI services
• Azure AI Search
• Azure Document Intelligence
• Azure AI Foundry
• FastAPI or Flask
• Docker containers
• Kubernetes basics
• Vector databases (Qdrant, pg_vector, Azure AI Search)
• Async Python programming
• Event-driven architectures and messaging systems
• Pandas and data processing libraries
• GitHub Actions or Azure DevOps pipelines 

Policy statements:
www.pwc.com/ua/uk/about/privacy.html

At Bixter, we're building a connected platform for international recruitment and workforce training. AI is moving fast, and we need someone whose job is to stay ahead of it on our behalf: to know what tools like Claude, GPT, Copilot, and whatever comes next can actually do, and to turn that knowledge into real advantage for us, not just talk about it.

We're looking for an AI Enablement Engineer who is genuinely expert in the practical use of AI and can move between advising and building both for internal operation and customer facing digital products.

Jobs to be done

• Stay current on AI tools and capabilities (Claude, GPT, Copilot, n8n, and others), and know what each is actually good for
• Advise internal operation, leadership, product development, sales and marketing on how and where to use AI across the business
• Follow the market and trends in AI use in practice
• Build automated workflows in and around our CRM, connecting AI capabilities into everyday operations
• Build AI-powered dashboards and reporting tools
• Suggest new AI capabilities we could add to our ecosystem, and help scope what it would take to build them
• Understand code well enough to work at the AI level. reading and writing code when needed, but primarily working through AI tools and APIs rather than building everything from scratch
• Handle integrations and API work when a project needs it

Requirements

• Deep, hands-on experience with modern AI tools, you've actually used Claude, GPT, Copilot, and similar tools to solve real problems
• Comfortable moving between advising and building.
• Strong understanding of code and technical systems, even if you're not writing production software full-time
• Experience building automation or integrations connecting tools like a CRM to other systems
• Genuinely curious and follow AI developments closely
• Comfortable working directly with leadership and translating business needs into practical AI use
• Show case of the previous work

Experience working with Odoo platform is plus. 

We help with relocation process and finding accommodation while expenses should be covered by the candidate. 

The role
You will lead technical direction and hands-on delivery of cloud-native back-end systems, using AI to accelerate disciplined engineering. Partnering with the Product Manager, who owns business priorities and the product roadmap, you will turn complex, ambiguous goals into clear architectures and achievable delivery plans. You will guide and assist engineers, facilitate shared understanding, and remain close enough to the implementation to diagnose issues and contribute directly.

This role owns technical leadership, mentoring, and delivery accountability. Formal HR performance management is outside its responsibilities.

What you will do

• Analyze business workflows and requirements with clients and the product team. Surface contradictions, missing requirements, risks, and impractical assumptions before directing implementation.
• Lead architecture and technical specification development, including interface contracts and nonfunctional requirements. Establish shared engineering practices and guide the team in applying appropriate controls.
• Deconstruct complex problems into simpler components and incremental delivery plans. Facilitate resolution of ambiguity and competing perspectives so the team understands the chosen approach.
• Direct agentic development tools through bounded tasks and explicit instructions. Review generated changes and retain ownership of code quality and the overall solution.
• Explain architectural tradeoffs in terms of business value, delivery time, operating cost, reliability, and supportability. Choose among serverless, containers, and other deployment approaches based on the problem.
• Build automated validation and diagnostic capabilities. Work with QA and DevOps on release readiness, secure deployment, production support, and learning from incidents.
•  

Required experience and engineering foundations
7+ years of professional back-end engineering experience. The 12-month AI experience requirement below is part of this total.

• Strong computer science and software engineering fundamentals, grounded in substantial hands-on back-end development with a production stack such as C#/.NET, Python, or Node.js/TypeScript.
• Hands-on production experience with at least one of AWS, Azure, or GCP, including serverless compute, messaging, data storage, identity, observability, and deployment.
• Sound understanding of API design, service and module boundaries, SQL and NoSQL data modeling, distributed systems, concurrency, and event-driven processing.
• Practical experience with automated testing, code review, source control, CI/CD, infrastructure as code, application security, and diagnosing production problems.
• Ability to read, critique, debug, and modify code and resolve technical issues independently of AI. You remain accountable for designs, implementations, and outcomes regardless of how they are produced.
• Proven hands-on technical leadership: architectural decisions, mentoring, constructive technical review, and coordinating delivery through influence and collaboration. Strong traditional leadership plus demonstrated individual AI proficiency qualifies.
•  

Required experience with design time AI
Design-time AI means using AI during analysis, design, implementation, testing, and maintenance. We require practical proficiency in rigorous engineering across repeated changes to complex systems.

• At least 12 months of sustained professional AI-assisted software development within your overall engineering experience, including hands-on use of agentic coding tools such as Claude Code, Codex, or comparable tooling.
• Experience delivering production software with AI and maintaining it through multiple subsequent iterations. You can explain your specifications, architectural choices, change controls, validation, and lessons from failures. Vibe coding alone does not meet this requirement.
• Ability to apply disciplined, specification-driven development: clarify ambiguity with the appropriate owners, expose assumptions, define technical designs and acceptance criteria, and keep specifications, contracts, decisions, and implementation aligned.
• Effective delegation to AI: decompose work into bounded tasks, provide relevant context and constraints, anticipate misinterpretation, define acceptance criteria, and critically review outputs. Use adversarial review to challenge assumptions and surface gaps.
• Ability to discuss choosing models for analysis, implementation, and review based on capability, reliability, latency, and cost, and managing context and token consumption in development workflows.
• Understanding of how architectural boundaries, explicit interfaces, and contracts contain change. Explain how you would prevent or detect unintended rewrites, assess downstream effects, and maintain a complex application across iterations.
• Ability to discuss validation controls, their limitations, and when particular controls are mandatory or implementation choices. Recognize that AI-generated code and tests can share mistaken assumptions and explain how you would challenge them.

• Ability to describe how specific tools and workflows preserve shared project context and enable another engineer to continue the work. Willingness to learn and work with Altus Nova Assistant (ANA), Altus Team AI, and the AI technologies and frameworks we develop.

   

Required runtime AI understanding
Runtime AI means AI capabilities operating within deployed solutions. You must meaningfully discuss the concepts below and outline a basic production workflow. Practical runtime AI implementation experience is a strong advantage.

• Explain model limitations, context management, retrieval, structured outputs, tool use, and cloud-based agentic workflows, with the ability and commitment to mature into production implementation.
• Distinguish functionality best implemented with deterministic code from work suited to LLM reasoning. Discuss how the approaches can be combined within reliable systems.
• Discuss workload routing among models based on capability, reliability, latency, and cost. Explain context and token management and guardrails for budgets, retries, and agent execution limits.
• Discuss safeguards that reduce and detect hallucinations, including grounding, output validation, evaluation, and appropriate abstention or escalation when evidence is insufficient.
• Distinguish generating a recommendation from executing an action. Discuss least-privilege access, human review and approval, rejection paths, failure handling, observability, and recovery.

• Discuss protecting client information in development tools and runtime systems, including secrets management, prompt injection, untrusted retrieved content, and restrictions on agent access to tools and systems.
  You will lead selection and design of technical controls for the team, engaging relevant specialists when a solution requires deeper expertise.

   

Communication and collaboration
- Strong spoken and written English is required. You must explain complex concepts in plain language, listen carefully, ask precise questions, and communicate effectively with client executives, subject-matter experts, and engineering teammates. Constructively challenge flawed specifications and work with their owners to resolve them.
- You must help others reason through ambiguity, incorporate differing perspectives, and build a shared understanding of the architecture and delivery plan. Delegation requires clear guidance, appropriate review, and support for the people doing the work.
- You will work with Product Managers, Business Analysts, architects, designers, front-end engineers, QA, and DevOps. We value constructive debate, clear decisions, and helping teammates succeed. Engineers engage directly with clients, participate in planning and estimation, demonstrate their work, document decisions, and track time accurately. Production reliability is a shared priority.

Preferred experience

• C#/.NET development and experience adapting across back-end languages and frameworks.
• Production AI workflows, including model routing, retrieval, evaluations, human approval, and cost controls.
• Legacy modernization, third-party integrations, or business-critical systems in complex client environments.

• Guiding teams in AI-assisted engineering and improving shared development workflows.

   

How we assess candidates
Our process includes a collaborative, real-time whiteboard session where you analyze unfamiliar problems, clarify ambiguity, and explain your approach with the interviewers. Candidates who pass complete a practical task using AI and walk the team through the resulting specifications, implementation, and validation. You must demonstrate independent reasoning, understand the outputs, and be able to take responsibility for the outcome.

Computer Vision Engineer

About Farsight Vision

Farsight Vision develops AI-powered geospatial intelligence solutions for defence and security operations. The platform transforms raw aerial and sensor data into real-time 3D environments, actionable analytics, and AI-assisted operational scenarios, enabling enhanced situational awareness, mission planning, and faster decision-making for both human operators and autonomous systems.

We operate at the intersection of computer vision and GIS, and if that interests you, read on.

We are looking for an experienced Computer Vision Engineer to own the design, development, and deployment of advanced CV algorithms – with a particular focus on GIS applications, image synthesis, and real-time perception pipelines. This is a hands-on engineering role in a startup where theoretical knowledge without execution has no value. You will work across the full pipeline: from data collection and preprocessing through model development and production deployment.

Responsibilities

• Design, develop, and deploy production-ready computer vision algorithms for image and video analysis in GIS-related applications
• Build end-to-end perception pipelines – data collection, preprocessing, model development, deployment, and monitoring
• Integrate CV components into operational products in close collaboration with cross-functional engineering teams
• Optimize algorithms for performance, reliability, and scalability in real-time and resource-constrained environments
• Develop and deploy Visual Place Recognition (VPR) systems for geo-localization and scene understanding tasks
• Implement and optimize CV algorithms on embedded and hardware-accelerated platforms, ensuring stable and efficient inference at the edge
• Process and analyze large-scale datasets for model training, validation, and continuous improvement
• Diagnose and resolve complex issues across computer vision applications in production
• Contribute to internal research, exploring emerging techniques in image synthesis, manipulation, and applied ML.

Requirements

• Expert-level Python – this is our primary engineering language. You must be comfortable writing clean, efficient, production-quality Python code
• 5+ years of hands-on experience in computer vision and applied machine learning
• Deep working knowledge of core CV and ML libraries: OpenCV, PyTorch, TensorFlow, and related tooling
• Solid understanding of machine learning, deep learning, and model development workflows end-to-end
• Hands-on experience with Visual Place Recognition (VPR) algorithms and techniques, including descriptor-based retrieval, sequence matching, and localization under varying conditions
• Proven ability to port, optimize, and run CV/ML models on embedded devices and edge hardware (e.g., NVIDIA Jetson, Raspberry Pi, or similar platforms)
• Proven experience with image processing, model training, and evaluation methodologies
• Ability to translate research into reliable engineering outputs with minimal supervision
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field – or equivalent demonstrable experience
• Strong analytical thinking and clear communication in a cross-cultural, fast-moving team.

Nice to have

• Experience with graphics APIs: OpenGL, OpenGLES, or Direct3D
• Background in graphical algorithms, 3D rendering, or computational geometry
• Familiarity with embedded systems or hardware-accelerated processing (TensorRT, ONNX Runtime, OpenVINO)
• Experience with VPR frameworks such as NetVLAD, SuperGlue, or HLoc

Security Eligibility

Our platform is actively used by the Armed Forces in live operations. As an Estonian-Ukrainian defense technology company handling sensitive operational data, we have a responsibility – legal, ethical, and practical – to ensure the integrity of everyone on our team. 

All candidates must be able to confirm the following:

• Neither you nor your close relatives (parents, spouse, siblings, children) reside in Russia, Belarus, or temporarily occupied Ukrainian territories
• You have no regular personal, financial, business, or professional contact with individuals in those territories
• You consent to a deeper security verification if the process advances to later stages

If any of the above criteria are not met, please do not proceed with your application.

Why Farsight Vision

We are a startup operating under real-world conditions – our product is in active deployment, and the pace reflects that. We are not building for a demo. Estonia is one of the most digitally advanced and defense-conscious countries in Europe – and Tallinn is increasingly home to serious defense tech. If you want to work on a problem that is hard, urgent, and consequential, this is the right place.

Flexible working hours. Paid vacation and sick leave. Direct access to founders and leadership

Application Process

1. Submit your CV and a brief cover letter explaining your interest and relevant experience
2. Complete a technical assignment designed to reflect the real problems we solve
3. Interview with our technical team and leadership

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Join PwC's Advanced Technology Solutions team as an AI Engineer, where you will contribute to AI and data science solutions for leading global clients. This role is suitable for developers and engineers who want to build, deploy, and scale machine learning systems and AI-powered applications in a dynamic consulting environment.

We are looking for candidates who are strong in Python, confident working with data, and capable of turning complex business challenges into reliable, production-ready AI solutions while collaborating with clients across Western Europe and the USA.

Key Responsibilities:

• Design, develop, and deploy AI and Machine Learning solutions. 
• Build Python-based applications leveraging Generative AI, LLMs, RAG, NLP, Computer Vision, and Data Science techniques. 
• Participate in the full project lifecycle, from requirements gathering through deployment and ongoing support. 
• Collaborate with clients and internal teams to understand business challenges and translate them into scalable technical solutions. 
• Work with structured and unstructured data to develop AI-driven applications. 
• Actively leverage AI-powered development tools such as GitHub Copilot, Cursor, Claude Code, and ChatPwC to enhance productivity, improve code quality, accelerate delivery, and solve complex problems responsibly. 

What You Bring:

• 1–2+ years of experience in AI, Machine Learning or Software Engineering. 
• Strong Python programming skills (e.g. pandas, numpy, scikit-learn). 
• Hands-on experience with Generative AI, LLMs, RAG, NLP, Machine Learning, or Computer Vision. 
• Experience working with SQL databases. 
• Understanding of the ML lifecycle, including model training, evaluation, deployment, and monitoring. 
• Strong analytical and problem-solving skills. 
• English B2+. 

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

Reelly AI is a B2B platform in the real estate sales sector that has become one of the market leaders in the UAE in just four years. More than 74,000 agents have registered on the platform. We help them find up-to-date information on more than 2,000 projects from developers in Dubai, Abu Dhabi, and Ras Al Khaimah.

Our business is selling data and access to our proprietary AI ecosystem. It helps developers see supply and demand in real time, understand agents’ needs, and make commercial decisions faster.

We work with international companies, including those from India, Pakistan, and the United Kingdom, that operate in the UAE. We are preparing for international expansion in cooperation with government partners. Our goal is to attract one million agents over the next three years.

I am writing this job posting personally. My name is Vitalii Ryzhak, and I am the founder and CEO of Reelly AI.

Recently, the real estate market in the region has experienced significant stress. For us, this period has become a catalyst for growth: developers have started digitizing their processes more actively, and we have received a large influx of new contracts. That is why I am resuming the search for new talent to join our team.

We are looking for a hands-on Head of AI & Business Automation who will report directly to me, the CEO, and turn opportunities for internal automation into reliable systems that people use every day.

You will own the strategy, implementation, adoption, and measurable business results of AI automation across Sales, Support, Customer Success, onboarding, CRM, and data operations. You will personally build the first production agents and workflows, working with our CTO and Product team on architecture, security, and alignment with the customer-facing roadmap.

What you will do

• Map processes with their owners, identify bottlenecks, and establish a baseline for time, cost, errors, and service quality
• Prioritize an automation backlog by expected business value and effort; decide when to build, buy, or improve an existing process
• Build and launch agents, integrations, and workflows using APIs, webhooks, and company data; address data quality before scaling
• Make systems dependable: test output quality, monitor usage and costs, keep logs, handle failures and retries, and provide human review or handoff where needed
• Work with the CTO on safe data access, permissions, and security; choose straightforward rule-based automation when an LLM is unnecessary
• Help process owners adopt new workflows through documentation, training, and clear ownership; measure actual results after launch
• Manage priorities and ongoing reliability, and help recruit and lead a small team as needs become clear

Who we are looking for

• Someone who can show 2–3 production AI or automation cases used by real people, explain their personal contribution, and share before-and-after results
• Practical ability to build with Python or TypeScript, SQL, REST APIs, and CRM systems
• Good judgment about when to use an LLM, a deterministic workflow, or human involvement
• Experience delivering reliable business systems, with attention to data quality, access safety, testing, monitoring, and operating costs
• Someone who can independently work with technical and non-technical teams, explain trade-offs, and communicate clearly in English
• Strong ownership: you can turn an unclear business problem into a prioritized plan, ship a working solution, and measure its effect

Experience in B2B SaaS or a data/API business, Sales, Customer Success, Support, or leading a small team will be an advantage. Familiarity with n8n, Make, Zapier, MCP, or RAG is useful where it solves a real problem.

The first 90 days

We would expect you to establish process baselines and a prioritized backlog, launch an initial pilot, and work toward 2–3 production workflows with clear owners, monitoring, and measured results. We will agree on the scope and success measures together based on the opportunities you identify.

Why this role may interest you

• Direct collaboration with the founder and influence over decisions
• Working at a fast-growing product startup that is already a leader in the international market
• Experience in a field involving some of the world’s most expensive real estate, investments, AI, data, marketing, and rapid growth
• A high salary, bonuses, and company shares. Full transparency and a young team
• Opportunities for business travel: we have already launched operations in Thailand, Indonesia, the Maldives, Georgia, and other destinations

My recommendation:

If you want the opportunity to join our team, apply for this role on Djinni. Details of the next stage and an invitation to a call will be shared with applicants through Djinni. On this call, I will introduce you to our company and all the opportunities within it: our corporate culture, challenges, results, and possibilities.

I, Vitalii Ryzhak, will be speaking on this call, and my goal is to make you fall in love with our mission just as I did six years ago. I believe that only the strong win. And we are building our strength in attracting international capital so that, when the time is right, we can focus all our efforts on rebuilding Ukraine.

Glory to Ukraine! Glory to the Heroes!

On behalf of our Client, Mobilunity is looking for a Senior AI / ML Engineer.

Our client is a high-growth, award-winning African nonprofit on a mission to radically transform healthcare access. The organization works to strengthen the potential and resilience of adolescent girls across Africa by building local health ecosystems that provide stigma-free, no-cost, quality-assured healthcare services.

Their technology platform connects community organizations, healthcare providers, and retail partners by enabling referrals, verifying service delivery, facilitating payments, and generating real-time data.

The organization operates across Kenya, Ethiopia, Uganda, Burkina Faso, South Africa, and Nigeria, with additional offices in Portugal, the Netherlands, and the United Kingdom. The global team consists of more than 250 international colleagues and works in a fast-paced, informal, and collaborative environment.

The role focuses on one of the organization’s critical scaling challenges: risk and fraud on the platform. It combines strong software engineering and data infrastructure skills with deep hands-on experience building and deploying modern AI and LLM-based systems in production.

Key Responsibilities:

Agentic Systems & GenAI Engineering

• Design, deploy, and debug sophisticated agentic AI workflows with multi-step reasoning, memory integration, and Model Context Protocol (MCP).
• Build and operate multi-agent systems using LangGraph, LangChain, or equivalent frameworks.
• Architect and continuously improve Retrieval-Augmented Generation (RAG) pipelines, including chunking strategies, retrieval mechanisms, and end-to-end evaluation.
• Deploy and operate LLM-based services in production.
• Optimise LLM systems for latency, throughput, reliability, and cloud costs using technologies such as LiteLLM, vLLM, SageMaker, or Bedrock.

Production ML & Engineering

• Develop traditional machine learning models for structured data, including classification, regression, ranking, and/or NLP use cases.
• Write clean, maintainable, production-quality Python code that integrates with the wider data and software engineering ecosystem.
• Work with large-scale structured datasets using complex SQL queries and data pipelines.
• Design and maintain evaluation and monitoring approaches for AI/ML systems.
• Contribute to team rituals, technical documentation, and shared engineering practices.
• Build systems with appropriate failure handling, monitoring, and graceful degradation.
• Take ownership of solutions from initial design through production operation and continuous optimisation.

Requirements:

• 5+ years of professional experience as an ML Engineer, Data Scientist, AI Engineer, Software Developer, or a similar role.
• Proven experience shipping and operating production software.
• Outstanding proficiency in Python.
• Strong experience working with large-scale structured data using SQL.
• Proven practical experience building and serving LLM-based or agentic AI systems for real users in production, rather than only developing internal prototypes.
• Hands-on experience with agent orchestration, multi-step AI workflows, or similar production GenAI systems.
• Solid understanding of traditional machine learning, with strong expertise in at least one area such as tabular ML, NLP, or deep learning.
• Strong understanding of production ML systems, including reliability, monitoring, evaluation, and optimisation.
• Strong verbal and written English communication skills.
• Ability to work independently, move quickly through iterative feedback loops, and take ownership of business outcomes.

Nice to Have:

• Experience in Risk, Fraud, Credit, Insurance, Cybersecurity, Fintech, or similar domains.
• Experience with GenAI observability, drift detection, and evaluation frameworks such as LangSmith, Evidently, or RAGAS.
• Hands-on experience with AWS environments and MLOps automation.
• Experience with containerisation and CI/CD for machine learning systems.
• Experience with LLM serving and optimisation using tools such as LiteLLM, vLLM, SageMaker, or Bedrock.
• Experience with LangGraph, LangChain, MCP, or multi-agent frameworks.
• Experience mentoring junior engineers or contributing to the wider technical community through blogging, talks, or public speaking.

N-iX is looking for a Senior Applied ML Engineer to support our client's Data Licensing team, which develops training datasets for frontier AI labs. You will evaluate and productionise existing ML models and services to deliver customer-requested metadata enrichment for data licensing opportunities, supporting the next generation of AI applications.

Responsibilities:

• Partner with the Principal Data Scientist and Principal Data Engineers, senior technical leaders and data scientists to implement and evolve model-evaluation and productionisation standards; independently own assigned enrichment workflows from evaluation through production delivery.
• Evaluate candidate models on representative content, using appropriate quality measures and threshold analysis to support selection and release decisions.
• Develop tested, maintainable Python inference components that conform to shared engineering frameworks, metadata contracts and deployment standards.
• Support ad-hoc metadata backfills by validating model outputs, estimating inference cost and throughput, and resolving model-specific processing issues.
• Work with data engineers to move enrichment components from representative evaluation to reliable corpus-scale execution.
• Assess model licensing, data-handling constraints and provenance requirements, ensuring enrichment outputs are reproducible and suitable for commercial use

Requirements:

• 6+ years of experience in applied ML, ML engineering, data science or software engineering, including hands-on experience delivering production ML inference systems.
• Experience evaluating pretrained or third-party ML models, defining appropriate quality metrics and operating thresholds, while balancing model quality against inference cost, throughput and operational complexity.
• Strong Python software engineering skills, including testing, packaging and dependency management.
• Hands-on proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.
• Experience developing, deploying and maintaining high-performing, resilient and scalable ML inference systems across CPU and GPU environments in both AWS and GCP
• Experience troubleshooting and optimising model execution in distributed, cross-cloud workflows.
• Clear communication skills and experience building consensus with technical and commercial partners.

Nice to have:

• Model tracking and lifecycle tooling such as MLflow.
• Managed ML and batch-inference platforms such as SageMaker, Vertex AI or Databricks.
• Experience evaluating models for image, video or audio content.
• Experience with Snowflake, DBT or Clickhouse

We are looking for an experienced Principal AI Engineer to lead the architecture, technical strategy, and evolution of enterprise-scale AI platforms and GenAI-powered solutions. The role requires strong hands-on experience with production AI systems, RAG, AI orchestration, distributed platforms, and AI engineering standards.

Responsibilities

• Define and own the architecture of enterprise-scale AI platforms
• Design and develop production-grade GenAI systems and AI-powered solutions
• Lead the development of RAG pipelines, retrieval infrastructure, and AI orchestration frameworks
• Design scalable distributed systems, APIs, data pipelines, and event-driven architectures
• Establish standards for AI quality, evaluation, observability, governance, and model lifecycle management
• Define and scale AI-driven software-development practices, including tools, guardrails, and automation patterns
• Drive architecture decisions and technical alignment across multiple engineering teams
• Build reusable AI platform components, frameworks, and internal tooling
• Conduct architecture and code reviews and mentor senior and Staff-level engineers
• Collaborate with product, data, security, infrastructure, and engineering teams
• Document architectural decisions, technical standards, and organizational best practices

• Lead technical initiatives across distributed international teams

   

Requirements

• 12+ years of professional software-engineering experience
• Significant experience working at Staff or Principal Engineer level
• Strong hands-on experience building and deploying production-grade GenAI / LLM systems
• Expert-level Python engineering skills
• Strong experience with LLM applications, RAG, vector databases, and retrieval infrastructure
• Experience with LangChain, LlamaIndex, semantic search, or similar AI frameworks
• Strong understanding of AI evaluation, model lifecycle management, observability, and MLOps
• Proven experience designing and evolving large-scale distributed systems
• Strong knowledge of APIs, data pipelines, event-driven systems, and high-scale platforms
• Experience driving architecture and platform initiatives across multiple teams
• Hands-on experience with AI-assisted development tools such as Copilot, Claude Code, or Cursor
• Strong engineering fundamentals in code quality, testing, CI/CD, and observability
• Ability to influence technical decisions and drive alignment without formal authority
• Experience collaborating with distributed teams across different regions and time zones

• Professional English, Upper-Intermediate or higher

   

Nice to have

• Experience building enterprise AI platforms or internal AI developer platforms
• Experience with Kubernetes, cloud platforms, and infrastructure automation
• Experience with MLOps platforms and model monitoring
• Experience with event-driven architectures and large-scale data processing
• Experience establishing AI governance and engineering standards across organizations
• Experience working with distributed teams across the US, China, and LATAM
• Experience in enterprise SaaS, FinTech, healthcare, or other complex domains

We’re looking for an experienced developer to build an AI assistant that users can interact with through text messaging. The assistant will connect to our existing database, answer questions using our information, handle follow-up questions, and send personalized news updates based on users’ interests.

The experience we’re aiming for is similar to texting an assistant like Instinct or Muse, with a focused scope: answering questions using our existing database and delivering personalized news updates.
 

You’ll take ownership of the technical setup, integrations, and development, working with our team to launch an initial version. Our target is a working pilot within approximately one month, with the scope finalized together.
 

You should have strong Python/Django experience and hands-on experience integrating AI models, APIs, and databases. Experience with Twilio or similar messaging platforms is important, along with building secure account access, subscription permissions, and scheduled notifications.
 

We’re looking for someone who has built and launched practical AI applications and can make sound technical decisions, communicate clearly, and identify potential issues early. Accuracy is essential: the assistant needs to retrieve reliable information from our data and handle unclear questions appropriately.
 

When applying, please share examples of relevant applications you’ve built, explain your specific role, and describe the tools you used. Please also include your availability over the next month and your hourly rate or estimated project budget.

Are you energized by walking into a client’s operation, finding the workflow that’s actually holding them back, and rebuilding it so AI handles the parts that don’t need a person? At Sigma Software, we don’t just add AI on top of existing processes  we redesign how the work gets done, with AI built into the operating logic from day one.

We’re looking for a Forward AI Deployment Engineer to own that redesign end to end: embedded with the client, hands-on with whatever automation the workflow actually needs, and accountable for turning a real operational problem into something running in production not a demo, not a pilot. Each engagement is built to leave something behind for the next one patterns, infrastructure, governance that already held up in production  so the second engagement doesn’t start from zero, and the tenth looks nothing like the first.

Requirements

• Proven experience taking AI systems from prototype to production inside a real operating environment, not just in a lab or sandbox.
• You treat LLM/RAG architectures, agentic systems, cloud platforms, and data pipelines as tools for redesigning how work gets done, not as the deliverable — and you’re strong and current enough with all of them to actually use them that way.
• Comfort mapping decision logic that’s partly undocumented, and judgment about where automation should stop and human accountability should start.

• Excellent communication and stakeholder management — able to advise a client directly and escalate without being asked.

   

  Responsibilities

   

• Embed directly with the client’s operational team to find the workflow that’s actually costing them time, quality, or money before recommending any tooling.
• Own the redesign end to end: rework the decision flow and handoffs around AI, then take the resulting system into production yourself.
• Translate a vague, cross-functional business problem into a concrete technical plan the client’s team can actually execute against.
• Prototype fast enough to show the client what’s possible, then build only the parts of that prototype the redesigned workflow actually needs.
• Where the redesign calls for it, build the agentic systems, RAG pipelines, or custom data pipelines that make it real never a deliverable in itself, always because the workflow needs it running in production.
• Manage stakeholder alignment across the client’s org, escalating early and requesting support before a blocker becomes a delay.
• Build up the client’s own team alongside the system pair with their people, explain the reasoning behind each decision, and leave them able to run and improve what you built after you’ve moved to the next engagement.
• Build the feedback loop from day one  telemetry, evaluation pipelines, human-in-the-loop review — so the system keeps improving after you’ve moved on.

We’re looking for an Applied AI Engineer (Squad Lead) to build production-grade AI agents and applications for an international fintech company operating across multiple markets.

This is a hands-on role where you’ll turn real business challenges into AI-powered solutions — from idea and POC to production and continuous improvement. You’ll work directly with business stakeholders, use AI-native development tools daily, and help shape the team as it grows.
 

What you’ll do:

• Build and deploy AI agents using LLMs, RAG, tool calling, memory, and multi-agent orchestration.
• Develop end-to-end applications, APIs, and integrations with internal systems.
• Design AI pipelines for data ingestion, embeddings, and retrieval.
• Own production systems, from architecture and deployment to monitoring and optimization.
• Collaborate with business stakeholders and mentor engineers while staying hands-on.

What we’re looking for:

• 7+ years of software engineering experience in backend or full-stack development.
• Experience leading engineers or owning a technical domain.
• Proven experience deploying AI agents and LLM-powered systems to production.
• Daily use of AI-native development tools such as Cursor or Claude Code.
• Strong system design, cloud architecture, and frontend/backend skills.
• Experience with vector databases, embeddings, and AI orchestration.
• Fluent English and strong communication skills.

Nice to have: LangGraph, LangChain, LangSmith, experience with regulated environments, and AI evaluation frameworks.

If you enjoy building AI systems that solve real business problems and make it to production, let’s talk!

The project. A UK startup founded by experienced founders with successful startups behind them, now closing its funding round. Their AI agents interview a company's employees about how they work, map the organisation's processes, and then build and run agents that automate them. That includes the infrastructure, integrations with Slack and Teams, and dashboards showing hours saved and the return on AI.
 

The team. It's small and very advanced in AI-driven development (about 100 PRs a week with agents). It has a senior CTO and a fast junior engineer, and needs a strong senior engineer in between.
 

What you'll do. This is a hands-on role, not management. You'll own the quality of the LLM product (evals, prompts, conversation quality, guardrails), improve the AI dev process, and design parts of the system (RAG, memory, agent security).
 

Must-haves:

• You've shipped production LLM products, ideally conversational or agentic
• Hands-on experience with evals
• Strong system design for LLM systems
• Fluent in agentic development
• Good English

• Full focus on this project

   

Nice to have:

• Microsoft Teams / SharePoint / Graph API integrations
• Voice agents
• Knowledge graphs
• Experience with GDPR, SOC 2 or the EU AI Act
• Early-stage startup experience
   

We offer:

• 15 paid day-offs per year.
• 10 UK/UA holidays.
• Flexible schedule and fully remote work from anywhere with reliable overlap.
• Minimal bureaucracy, high authonomy and trust, fast decisions.
   

Approaching stages:
1. Two-way Q&A with me.
2. Meet & Greet with their СТО.
3. Meet & Greet with their Team.
4. ...
5. PROFIT

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

We are looking for someone who:

🔹Uses advanced AI coding tools and agents as an integral part of the software development lifecycle.
🔹Knows how to use AI effectively for coding, debugging, testing, code exploration, refactoring, documentation, and technical research.
🔹Can design effective workflows around AI rather than relying on simple prompting.
🔹Can identify engineering tasks and processes that can be automated or significantly accelerated with AI.
🔹Understands both the capabilities and limitations of AI-generated code and applies strong engineering judgment when reviewing and deploying it.
🔹Bonus: has built internal AI tools, agents, automation workflows, or AI-powered product capabilities.
 

Key Requirements:

🔹 5+ years of professional software development experience, primarily in backend development;
🔹 Strong experience designing and building production-grade services and APIs;
🔹 Strong software engineering fundamentals, including system design, data structures, clean code, and scalable architecture;
🔹 Strong experience working with C# / .NET ;
🔹 Strong experience with SQL and relational databases, preferably MySQL;
🔹 Experience working with AWS or other cloud platforms;
🔹 Experience with distributed systems, high-scale environments, and production troubleshooting;
🔹 Experience integrating with complex external APIs and third-party platforms;
🔹 Strong ownership mindset — comfortable taking a problem from initial definition through production;
🔹 Strong communication and collaboration skills;
🔹 Ability to independently explore unfamiliar domains and technologies and quickly turn them into working solutions;
🔹 English – Upper-Intermediate or higher.

What you will do:

🔹Design, develop, and own scalable backend services and APIs supporting our social advertising capabilities;
🔹 Build and maintain integrations with leading social platforms such as Meta, TikTok, YouTube, and other advertising ecosystems;
🔹 Take end-to-end ownership of features — from technical design and implementation through production rollout, monitoring, and optimization;
🔹 Work with complex third-party APIs, authentication flows, data models, platform limitations, and constantly evolving external integrations;
🔹 Build reliable, high-scale distributed services operating in a cloud production environment;
🔹 Develop a deep understanding of the product and business use cases, and contribute to product and technical decisions — not only implementation;
🔹 Identify opportunities to simplify systems, automate processes, and improve engineering velocity;


Interview stages:
🔹 HR Interview YozmaTech;
🔹 Technical Interview;
🔹 Live Coding Session;
🔹 Interview with CTO;
🔹 HR Interview;
🔹 Reference Check;
🔹 Offer.