Jobs ML / AI

We are looking for a talented AI Engineer to join our growing engineering team and help build intelligent systems powered by modern machine learning and generative AI technologies. You will design, develop, and deploy AI-powered features that enhance products, automate workflows, and deliver data-driven insights. This role is ideal for engineers who enjoy working at the intersection of software engineering, machine learning, and scalable cloud infrastructure.

Details

Location: Remote (Europe)
Employment Type: Full-time / Contract
Start Date: ASAP
Language Requirements: English – Upper-Intermediate or higher

Key Responsibilities

Design and implement AI-powered applications and services.

Develop and deploy machine learning and generative AI models.

Integrate LLM APIs (OpenAI, Anthropic, open-source models) into products and internal tools.

Build data pipelines and systems to support model training and inference workflows.

Optimize model performance, latency, and cost efficiency.

Collaborate with product, engineering, and data teams to translate business needs into AI solutions.

Monitor and maintain AI systems in production environments.

Requirements

3+ years of software engineering experience.

Strong proficiency in Python.

Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.

Experience integrating LLMs or generative AI solutions.

Knowledge of data processing and model deployment workflows.

Familiarity with cloud platforms (AWS, GCP, or Azure).

Strong understanding of software architecture and APIs.

Nice to Have

Experience with LangChain, LlamaIndex, or AI orchestration frameworks.

Knowledge of vector databases (Pinecone, Weaviate, FAISS).

Experience with RAG architectures.

Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).

Experience building AI agents or automation systems.

Requirements

Overall:
Strong knowledge of Python, TensorFlow or PyTorch.
Bachelor's degree in Computer Science (or related field).
Experience with Machine Learning, Gen AI and Computer Vision.
Experience with python web services.
Experience with cloud ML deployment.
Strong understanding of model training, evaluation, and optimization.
Experience with AWS or GCP or Azure

LLM:
Experience with LLAVA or ChatGPT or LLAMA or Gemini.
Fine-tuning open-source LLMs.
Deploying open-source LLMs.
Familiar with agents.

Computer Vision:
Expertise with tracking, keypoint/pose estimation, action recognition, and depth estimation.
Experience in image and video processing using OpenCV.
Hands-on experience with YOLO and Transformer-based architectures for vision tasks.

Will be a plus:
Data Version Control for Big Datasets.
Optimizing models for edge devices.
C++, Java knowledge a plus

Other:
Ability to multi-task, organize, and prioritize work effectively.
Upper Intermediate or higher level of English proficiency.

What We Offer:
- Competitive salary based on experience and skills.
- Flexible working hours and the possibility to work remotely.
- Opportunities for professional growth and career advancement.
- Friendly and collaborative team environment.
- Access to the latest technologies and tools.

 

We are looking for an experienced AI Solution Architect to lead the design and delivery of scalable AI solutions built on Microsoft Azure. In this role, you will work closely with business stakeholders, customers, and engineering teams to transform complex requirements into robust AI architectures and production-ready solutions.

You will play a key role in defining architecture standards, guiding delivery teams, and supporting pre-sales initiatives in a consulting-driven environment.
 

Key Responsibilities

AI Solution Architecture

• Lead the end-to-end design of AI solutions based on Microsoft Azure
• Translate business and functional requirements into scalable and secure technical architectures
• Design and validate AI architectures including Retrieval-Augmented Generation (RAG) solutions
• Define and enforce architecture standards, best practices, and governance
   

Technical Leadership

• Act as a trusted technical advisor for customers, internal stakeholders, and delivery teams
• Provide technical leadership and quality oversight throughout the delivery lifecycle
• Support pre-sales activities, including solution design, estimations, and technical proposals
   

Solution Design & Delivery

• Design integrations with Azure AI services and enterprise systems
• Create architecture diagrams, solution blueprints, and technical documentation
• Lead development and validation of PoCs and pilot implementations
• Contribute hands-on to coding, testing, and CI/CD pipeline configuration
   

Required Experience & Skills

• Strong experience designing end-to-end AI solutions on Microsoft Azure in a consulting environment
• Proven background in AI solution architecture, including Generative AI and RAG-based architectures
• Hands-on experience with Azure AI services, including:
  • Azure OpenAI
  • Azure AI Search
  • Azure Cognitive Services
• Solid understanding of Azure PaaS services and cloud architecture principles
• Experience creating architecture diagrams, technical blueprints, and solution estimates
• Experience building PoCs and pilot solutions
• Hands-on experience with coding, testing, and CI/CD pipelines
• Strong communication skills and ability to work as a technical advisor for customers and delivery teams
   

Nice to Have

• Experience in a Tech Lead role
• Experience working in factory-mode delivery environments
• Background in enterprise AI transformation projects

Numerical Technologies, a leading provider of software development and consultancy services for financial institutions, is looking for talented people experienced in Math and Python who will be responsible for development, testing, implementation, debugging and support of sophisticated financial applications.

Joining Numerical Technologies is a unique chance that provides the opportunity to work alongside experienced professionals on impactful, quantitative projects across North and South America, Europe, the Middle East, Africa, CIS and South Asia. This position is a chance to work hand-in-hand with expert quantitative researchers and quantitative engineers to create and implement research and simulation tools that leverage existing automated trading software and sophisticated statistical techniques and technologies.

Do you enjoy the process of problem solving, a process where you recognize areas of improvement and iterate and innovate to improve? Does your curiosity and desire to learn drive you? If this sounds like you, don't miss this opportunity to gain valuable experience in a highly competitive and demanding fintech industry.

What are we looking for?

◼️ Deep understanding of Applied Mathematics: Probability Theory and Statistics, Numerical Methods, Linear Algebra, Optimization

◼️ Bachelors, Masters or Phd in Physics, Mathematics, Statistics; or equivalent experience (we also welcome students)

◼️ At least 0.5 year of commercial experience as a Python Developer

◼️ Practical experience with AI technologies, particularly in applying them to solve real-world business problems
◼️ Basic understanding of NLP concepts
◼️ Familiarity with LLMs, embeddings, vector databases, and RAG architectures

◼️ Willingness to learn together with a team of professionals
◼️ Experience working with LLM APIs (OpenAI, Anthropic, Azure OpenAI, etc.)

◼️ Knowledge with Git, Jira, and Confluence

◼️ Excellent communication skills

◼️ Intermediate and higher level of English.

Please mention in your application any participation or awards in mathematics, physics, or programming Olympiads.

What will you be doing?

◼️ Collaborating with cross-functional teams to develop AI-driven solutions that address specific business challenges.

◼️ Continuously learning and staying updated on the latest AI technologies and best practices, applying this knowledge to improve existing projects.  

What additional skills will help you stand out?

◼️ Experience in Machine Learning

◼️ Participation in Kaggle competitions

◼️ Experience working at a financial institution

◼️ Experience working with cloud platforms (AWS, Azure)

We offer:

◼️ Competitive compensation depending on experience and skills

◼️ Regular assessments and salary reviews

◼️ Compensation for sick lists and regular vacations

◼️ Health insurance

◼️ English classes with certified English teachers

◼️ Flexible working schedule

◼️ Friendly team and enjoyable working environment

◼️ Comfortable, spacious office within 10 min from all three Metro lines.

◼️ Corporate and social events.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client's platform is designed to work with sales representatives and automate as much of their work as possible, in order to allow them to connect with their clients and make their communications faster. The company also provides intelligence to team managers with performance insights, allowing them to coach their sales reps more effectively.

About the role:
As a Machine Learning Engineer in the Conversational Intelligence Team you will be responsible for building systems that process real-time audio and text streams from Knowledge AI Assistant. You will build scalable machine learning platforms and systems to handle large quantities of data. Engineer low-latency and high-throughput ML systems that must scale for growing business.

Responsibilities:
- Working with voice streams and real-time transcriptions of voice streams to extract intelligence and actionable insights for customers
- Analyzing the relevance of extracted intelligence, performance of the extraction algorithms, and evaluating the performance of third party voice processing APIs
- Finding ways to engineer high availability into a system that has lots of moving parts, not all of which are directly under your control
- Working with stakeholders to make sure our customers have the tools they need to be successful on our platform
- Finding quick ways to prototype and test possible solutions to large problems
- Looking across the stack for the best return on investment for any given pain point.

Requirements:
- 4+ experience in Machine Learning sphere
- 2+ years of experience working with Natural Language Processing.
- Experience with cloud-based data platforms and continuous-deployment projects
- Experience with implementing machine learning pipelines
- Willing to go above and beyond to help other team members
- Ability to prioritize details along a path of iterative delivery
- Ability to quickly ramp up new technologies and start contributing.

Desirable:
- Experience with Go
- Experience building platforms from scratch

We offer:
- Competitive salary and perks; annual satisfaction survey and performance review
- Paid vacation and 100% paid sick leaves
- Work in a creative friendly environment using cutting-edge technologies
- Technical and product leadership opportunities

AI Tools & Development Workflow Advisor

Remote · Consulting or Full-time

We are looking for a senior specialist who deeply understands the modern AI development ecosystem and has hands-on experience applying AI tools in real commercial software projects.

This role is not about experimenting with new tools in isolation. We are looking for someone who knows how to use AI effectively in production environments, understands where these tools actually help, and where they introduce risks, limitations, or inefficiencies.

The goal of this role is to help our engineering team build faster, smarter, and more safely using modern AI-assisted development workflows.

What we need

We are looking for someone who:

• Has real production experience using AI tools in commercial software development
• Understands the limitations, risks, and failure modes of AI-assisted development
• Knows how to design practical workflows, not just experiment with tools
• Can help teams use AI responsibly and effectively
• Can balance speed, code quality, and maintainability

Responsibilities

• Review and assess our current development workflows
• Identify where AI tools can meaningfully improve productivity
• Design practical AI-assisted development workflows
• Help implement safe usage patterns for AI tools
• Define internal best practices and standards
• Train and mentor engineers on effective AI usage
• Help choose the right tooling stack for our team

Required experience

• Strong background in software engineering
• Experience working on commercial software products
• Practical experience using AI development tools in production environments
• Understanding of software architecture and engineering trade-offs

Relevant tool ecosystem (examples)

Experience with some of the following:

AI coding tools

• GitHub Copilot
• Claude / GPT development workflows

Developer productivity tools

• AI code review tools
• AI-assisted debugging
• automated documentation generation
• prompt-based development workflows

AI engineering workflows

• agent-based development flows
• structured prompting for development tasks
• AI-assisted refactoring and migration

What is important for us

We value people who:

• Think practically, not just theoretically
• Understand when AI tools should NOT be used
• Care about long-term maintainability
• Can help teams build reliable engineering processes

Engagement format

Flexible:

• Consulting engagement
• Technical advisor
• Part-time
• Full-time

About the project

We are building a complex B2B SaaS platform used to manage configuration, pricing, quoting, and sales workflows for customizable products.

Our goal is to build a high-performance engineering team that effectively leverages modern AI development tools while maintaining production-grade quality.

We are looking for a highly experienced Senior AI/ML Engineer to lead the creation of a next-generation real-time biometric estimation system for global sports broadcasts.

About the Project:
We are building a real-time, non-contact system to estimate athletes’ exertion for live sports broadcasts. Using high-speed video and computer vision, it predicts force metrics with 85%+ accuracy, replacing traditional sensors, with low-latency and robust performance under complex conditions.

Key Responsibilities:

Phase 0 – Pilot

• Design ML architecture for grip estimation
• Train initial model (force sensors + video data)
• Build training & data labeling pipeline
• Validate across diverse athlete profiles
• Achieve 75%+ correlation

Phase 1 – Demo

• Refine model using demo event data
• Implement 2-second per-athlete calibration
• Optimize for edge cases (skin tones, hand sizes)
• Achieve 80%+ correlation

Phase 2 – Production

• Improve accuracy toward 85%+
• Optimize inference to <40ms (P99)
• Implement advanced scoring features

• Production hardening & reliability improvements

   

Required Skills:

• 5+ years of experience in applied machine learning/deep learning
• Strong background in computer vision and image-based regression tasks
• Hands-on experience with PyTorch or TensorFlow for production systems
• Experience with real-time inference optimization (TensorRT, ONNX Runtime)
• Understanding of signal processing and temporal data analysis
• Experience training models on diverse datasets (handling bias, data augmentation)

• Proven track record achieving high-accuracy requirements (>80% on complex tasks)

   

  Strongly Preferred:

• Experience with biomechanical or physiological signal estimation
• Knowledge of optical/visual phenomena (skin blanching, perfusion, micro-tremors)
• Experience with few-shot learning or transfer learning approaches
• Background in sports analytics or human performance monitoring
• Experience with active learning for iterative model improvement

• Published research or patents in computer vision/ML domains

   

  Nice to Have:

• Experience with NIR (near-infrared) imaging or multi-spectral analysis
• Knowledge of pose estimation frameworks (MediaPipe, OpenPose)
• Experience with edge ML deployment on NVIDIA platforms
• Familiarity with time-series forecasting or sensor fusion

Soft Skills:

• Technical leadership: Ability to make critical architectural decisions under uncertainty
• Problem-solving: Creative approaches to novel ML challenges (no precedent for optical grip estimation)
• Communication: Clearly explain complex ML concepts to non-technical stakeholders
• Adaptability: Rapid iteration based on real-world performance feedback
• Ownership: Take full responsibility for model accuracy through systematic experimentation

About the Role

We are expanding our AI practice and are looking for a hands-on Lead AI Consultant who can step into real business contexts, understand how companies operate, and design practical AI Agent–based solutions that automate processes, reduce manual work, and improve efficiency.

We are looking for a consultant - someone who designs, builds, evaluates, explains, and delivers.

You will work across internal initiatives and client projects, collaborating directly with business stakeholders, department heads, and technical teams. 

Key Responsibilities

AI Agents & Automation

• Design and implement AI agents that act as technical/operational assistants (process execution, monitoring, decision support).
• Translate business problems into practical AI use cases using LLMs, APIs, and orchestration frameworks.

• Build end-to-end automation flows integrating AI agents with enterprise systems.

   

Business & Consulting Work

• Engage directly with business stakeholders and department heads to understand workflows, constraints, and priorities.
• Evaluate client businesses and map current IT and process landscapes.
• Propose realistic AI-driven improvements aligned with business goals, security requirements, and operational constraints.

• Support clients in adopting AI solutions, including explaining how systems work and how teams should interact with them.

   

Technical Design & Security

• Design AI solutions with a strong focus on security, compliance, and data protection, especially for enterprise and regulated environments.
• Work with APIs, system integrations, and data pipelines to ensure stable and scalable solutions.

• Make architectural decisions balancing speed, reliability, and long-term maintainability.

   

Research, R&D & Enablement

• Continuously research new approaches in LLMs, AI agents, orchestration frameworks, and automation tools.
• Participate in internal R&D initiatives and help shape internal best practices.
• Contribute to knowledge-sharing and educational activities (internal sessions, client workshops, presentations).

• Support product teams with AI expertise when needed.

   

Pre-Sales & Client Interaction

• Participate in pre-sales activities: technical discovery, solution design, estimations, and presentations.
• Help shape proposals and technical narratives for clients.

• Represent the company in client meetings as a trusted technical and business advisor.

   

Requirements

• Strong technical background (engineering, architecture, or senior technical consulting).
• Practical experience working with LLMs, APIs, and automation systems.
• Hands-on involvement in client-facing roles (consulting, solution delivery, pre-sales).
• Experience evaluating business processes and proposing technical solutions.
• Solid understanding of:
  • Generative AI & LLMs
  • AI Agents and orchestration concepts
  • APIs and system integrations
  • Business process automation
• Ability to quickly understand how a business operates and turn that understanding into working AI solutions.
• Strong communication skills - able to explain complex technical topics to non-technical audiences.
• Comfortable working in environments with rapid change and evolving requirements.
• Curious, pragmatic, and solution-oriented.

• Fluent English is required; additional languages (e.g., Arabic, Italian, German, French) are a plus.

   

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• MBA or equivalent business leadership training preferred.

This is us

At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.
 

This is the job

We are looking for an AI/ML Engineer to design, develop, and deliver a Proof-of-Concept (PoC) system that validates the use of Distributed Acoustic Sensing (DAS) and Automatic Identification System (AIS) data for detecting intrusions near subsea communication cables.

The solution will analyze acoustic signals from fiber-optic sensing systems together with vessel tracking data to identify potential threats to critical underwater infrastructure. The goal is to provide early warning capabilities, enabling timely intervention and protection of subsea assets.

This is you

• Strong experience in Machine Learning / AI development
• Strong programming skills in Python
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn
• Experience working with time-series data or signal processing
• Experience building ML pipelines for data processing and model training
• Knowledge of anomaly detection and pattern recognition techniques
• Strong analytical and problem-solving skills
• Good communication skills and ability to work in a distributed team

This is your role

• Design and develop machine learning models for analyzing DAS acoustic signals and AIS vessel tracking data
• Build a PoC system for intrusion detection around subsea communication cables
• Develop data processing pipelines for large-scale sensor and geospatial data
• Implement algorithms for anomaly detection and event classification
• Integrate multi-source data (DAS + AIS) for improved detection accuracy
• Perform data exploration, feature engineering, and model evaluation

We’re hiring an AI Agent Architect to design and build production-grade autonomous AI agents powered by LLMs. This role is for someone who has already shipped agentic systems, can architect multi-step reasoning pipelines, and knows how to make RAG reliable through evaluation, while optimizing cost at scale and addressing real-world failure modes.

What you’ll be responsible for

• Building and operating autonomous AI agents in production
• Designing multi-step reasoning pipelines (planning, tool-use, orchestration)
• Implementing RAG systems end-to-end and setting up evaluation to measure and improve quality
• Driving LLM cost optimization at scale (model selection, routing, caching/batching strategies, usage controls)
• Identifying and mitigating failure modes in AI systems (hallucinations, retrieval issues, tool errors, cascading failures)
• Designing multi-agent coordination patterns (specialized agents, handoffs, routing, communication protocols)
• Delivering these systems as cloud-native services (scalable, observable, resilient)Requirements (must-have)
• Proven experience building autonomous AI agents that run in production
• Experience designing multi-step reasoning and orchestration pipelines
• Hands-on implementation of RAG + evaluation (testing, metrics, and iterative improvement)
• Experience optimizing LLM costs at scale
• Strong understanding of AI system failure modes and practical mitigation approaches
• Experience with multi-agent coordination
• Experience building cloud-native systems (reliability, monitoring, scalable deployment)

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

And now we are looking for a ML Operations Engineer to join us as part of our team.

About the role:

PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others.

We are seeking an experienced and innovative engineer to expand and drive our Data Science and Machine Learning efforts in the EU and Ukraine.

Team setup: 1 Engineering Manager, 4 Senior ML Ops Engineers

Work Environment: The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert You will

• Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation
• Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment
• Design and deliver tasks end-to-end with little guidance from Senior team members
• Provide support to teams building and deploying AI applications by addressing common pain points in the MLDLC
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Support the vision and values of the company through role modeling and encouraging desired behaviors.
• Participate in various cross-functional company initiatives and projects as requested.

• Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance.

   

We’re looking for you if you have

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or commensurate experience)
• 3+ years of experience in hands-on development and deployment of Machine Learning algorithms and services
• 3+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 3+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 50% of:
  PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery, with practical understanding of containerization technologies such as Kubernetes and Docker
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools.
• Good problem-solving skills with a focus on innovation, efficiency, and scalability in a global context.
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions.
• Ability to be a team player who can also work independently

• Experience working across multiple development teams is a plus

   

Desired Skills

• Experience with cloud platforms (AWS, Google Cloud Platform, or Azure).
• Proficiency in GitOps practices and CI/CD pipeline development and management.
• Observability and monitoring: Integration experience with observability tools (Prometheus, Grafana) and building instrumented, production-ready systems.
• LLM Infrastructure: Experience provisioning and managing Large Language Models through managed services (Azure OpenAI, Google Vertex AI, Amazon Bedrock).
• LLM Tooling: Hands-on experience with LLM gateways (LiteLLM) and agentic frameworks (LangGraph, LangSmith, or similar).
• Vector Systems: Practical experience with vector embedding models and vector databases (Pinecone, Weaviate, Milvus, pgvector).
• RAG Systems: Experience building Retrieval-Augmented Generation systems and evaluating both retrieval quality and generation performance.
• Cloud-native experience with services like Amazon SageMaker, Google Vertex AI, or Azure ML
• Familiarity with ML frameworks and tools: PyTorch, TensorFlow, scikit-learn
• Experience with data infrastructure: Redis, Elasticsearch, Apache Kafka.
• ML experiment tracking and model management: Weights & Biases, MLflow, KubeFlow.
• API development with FastAPI or similar frameworks.

• Java programming experience is a plus.

   

What’s in it for You

Reveal great tech solutions

Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.

Experience an agile and flexible working environment

Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.

Embrace the opportunity for personal and professional growth

Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more.

Be among like-minded people

Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.

Interview steps

1. Pre-Screening with the recruiter
2. Tech Interview(ML Fundamentals, Software Engineering) + Live Coding (up to 1,5 hours)
3. ML System Design Interview (up to 60 min)
4. Interview with Engineering Manager (60 min)

We are currently looking for an AI Pro Code Developer to join a project for our client. This is an outstaff position, where you will work closely with the client’s engineering teams to design and implement AI-powered solutions within a modern cloud environment.

In this role, you will take ownership of the technical architecture of AI solutions, work with Azure and Azure OpenAI, and provide hands-on development and DevOps expertise while ensuring enterprise-grade scalability, security, and reliability.

Key Responsibilities:

• Define and own the end-to-end technical architecture for AI solutions built on Azure, Azure OpenAI, and Data Lake platforms
• Ensure alignment with customer IT standards, security policies, compliance requirements, and cloud governance frameworks
• Lead DevOps strategy, including CI/CD pipelines, infrastructure as code, monitoring, and automation
• Provide hands-on technical guidance and development using .NET and Python
• Collaborate with customer engineering and IT teams to ensure solutions meet requirements for scalability, performance, and maintainability
• Support and guide local developers and full-stack engineers within the project team

Requirements:

• 3–5+ years of experience in software engineering, cloud development, or solution architecture
• Strong experience with Microsoft Azure cloud ecosystem
• Hands-on experience with Azure OpenAI and AI-enabled architectures
• Experience working with data platforms and Azure Data Lake
• Strong software engineering skills in .NET and Python
• Solid DevOps experience, including:
• CI/CD pipelines
• Infrastructure as Code (IaC)
• Monitoring and automation
• Experience designing secure, scalable, enterprise-grade solutions
• Understanding of enterprise security patterns, governance, and cloud standards
• Ability to collaborate effectively with customer engineering and IT teams
• English level: B2+

We Offer:

✔️ Full-remote work

🏝 18 vacation days per year

🎁 Birthday celebration present

🧑🏻‍💻 Learning and development opportunities

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 now launching our next growth engine — AI-powered, automated, and data-driven.

This role is not about coordination. We are looking for a builder who will own and develop our end-to-end Outreach & GTM Engine.

Key Requirements:
🔹 2+ years of experience in SDR, Growth, RevOps, GTM, or Marketing roles;
🔹 Strong hands-on CRM experience (HubSpot / Monday — customization and workflow building);
🔹 Experience with automation tools (n8n, Zapier, Make, Clay, etc.);
🔹 Experience working with LLM workflows and AI tools (ChatGPT, Claude Code, etc.);
🔹 Builder mindset — able to ship fast;
🔹 High ownership and accountability;
🔹 Strong analytical thinking;
🔹 Clear communication skills;
🔹 Comfortable in a fast-paced scale-up environment;
🔹 Systems thinker, not just a task executor;
🔹 English — Upper-Intermediate or higher;
🔹 Experience in the tech outsourcing / R&D services industry;

Will be plus:
🔹 Experience building GTM systems from 0 → 1;

What you will do:
🔹 Build and optimize outbound and SDR automation systems;
🔹 Architect end-to-end CRM and GTM workflows (HubSpot / Monday);
🔹 Design and deploy AI agents for research, personalization, and qualification;
🔹 Improve funnel conversion rates and pipeline predictability;
🔹 Align GTM insights with Recruiting teams;
🔹 Drive measurable impact: more qualified meetings, lower cost per meeting, predictable pipeline growth;

Interview stages:
🔹 HR-interview;
🔹 Tech interview;
🔹 References;
🔹 Offer;

Why Join Us?
At YozmaTech, we know that great companies are built by the people who create the environment where teams can truly thrive.
We’re a global company expanding across multiple markets, and our internal teams play a key role in shaping how we grow, collaborate, and support both our clients and developers.
Here, your ideas matter. We encourage initiative, experimentation, and ownership. If you see a better way to do something — we want you to build it.
You’ll work closely with leadership, influence real decisions, and help develop new directions for the company.

From day one, you’ll get:
🔹 The opportunity to launch initiatives and shape internal processes
🔹 A collaborative international team that values ownership and trust
🔹 Exposure to global markets, startups, and innovative tech companies
🔹 Space to grow your role and take on new responsibilities as the company evolves

After You Apply
Our hiring process is clear and respectful.
You’ll always know who you’re meeting, what the role involves, and how you can contribute to the company’s growth.

Everyone’s Welcome
We believe diverse teams build stronger companies.
At YozmaTech, we create an environment where different perspectives are valued and everyone can grow.

Ready to grow with us?
Let’s talk.
Your next chapter at YozmaTech could start here.

Duck Agency helps businesses automate their operations using nocode / lowocBasic Docker / cloud ddeploymentea and AI. We build agents and workflows for operational, marketing, and sales teams — tools that actually replace manual work, not just demos.

We're looking for an AI developer who can build agents that analyze data, generate reports, take actions (send messages, update systems, create documents), and automate repetitive processes that people currently do by hand.

What you'll do:

• Build AI agents that automate end-to-end business workflows
• Process and summarize large datasets (CSV, tables, DB exports)
• Integrate agents with APIs, CRMs, Google Sheets, Slack, Telegram, and other tools
• Identify manual processes and turn them into automated pipelines

Requirements:

• Real experience building AI agents (not just API calls — actual agent logic with tools, memory, actions)
• Comfortable with structured data: SQL, CSV, Pandas
• Prompt engineering, function calling, tool use — you know what these mean in practice
• Ukrainian, Russian, or English — any one is fine

Nice to have:

• n8n, Make, Airtable, or Monday.com experience
• RAG pipelines, vector databases

Role Summary
You will play the role of a semantic architect behind our AI‑powered Knowledge Graph supporting flavor and beverage innovation. This role is responsible for designing ontologies, SHACL validation frameworks, and YARRRML mapping rules that enable structured, high‑quality, machine‑interpretable R&D knowledge. Working closely with flavor scientists, product developers, data engineers, and AI teams, the Ontologist will translate complex scientific concepts into formal knowledge models, maintain consistent terminology and synonyms across domains, and ensure that all R&D data can be integrated, reasoned over, and leveraged for advanced discovery and formulation insights. This position is central to accelerating innovation, improving knowledge reuse, and enabling next‑generation intelligent tools for the R&D organization.

Key Responsibilities

1.Ontology Design & Semantic Modeling
Work with business stakeholders to identify and maintain a set of competency questions that the ontology must support.
Design, extend, and maintain ontologies covering ingredients, flavors, sensory attributes, formulations, human trials, regulatory concepts, and experimental processes.
Perform conceptual modeling with domain experts and translate concepts into formal RDF/OWL semantics.
2. SHACL Constraint and Validation Framework
Develop and maintain SHACL shapes to enforce data quality, structural validity, consistency rules, and business constraints across the Knowledge Graph.
Collaborate with data engineers to validate incoming data streams using SHACL rules and produce validation reports.
3. YARRRML & Semantic Mapping Design
Design and maintain YARRRML mapping rules to transform heterogeneous R&D datasets into RDF/Knowledge Graph structures.
Work with data engineering teams to operationalize RML/YARRRML pipelines within ingestion workflows.
4. Knowledge Graph Integration & Reasoning
Collaborate with the development team to integrate ontologies into reasoning engines, entity extraction workflows, and semantic search pipelines.
Support entity alignment, relationship modeling, and enrichment algorithms that drive flavor discovery.
5. Synonym, Terminology & Vocabulary Management
Build and maintain synonym dictionaries, alternative labels, multilingual terms, and context-specific vocabulary used by flavorists and product developers.
Ensure synonym management is consistently reflected across ontologies, SHACL shapes, and mapping rules.
Facilitate terminology alignment workshops with subject matter experts.
6. Governance, Versioning & Documentation
Establish and maintain ontology governance including version control, documentation, and change-management workflows.
Maintain high-quality documentation, competency questions, term definitions, and modeling rationales.
Required Qualification

Proven experience with RDF, RDFS, OWL, and SPARQL.
Hands-on work with ontology editors (e.g., Protégé, TopBraid Composer).
Strong understanding of SHACL, RML/YARRRML, or equivalent mapping frameworks.
Experience in semantic modeling and conceptual data design.
Experience in food science, chemistry, sensory science, or CPG R&D domains.

Preferred Qualifications

Degree in Knowledge Engineering, Information Science, Semantic Technologies, Computational Linguistics, or related fields.
Knowledge of industry ontologies or semantic standards (e.g., SKOS, SAREF, DOLCE, IOF).
Familiarity with graph databases (e.g., Neo4j, GraphDB, Stardog) and knowledge-graph architectures.