Jobs ML / AI Engineer

Job Summary

We are seeking a highly organized and detail-oriented professional to support project planning, execution, and control. This role combines the functions of a coordinator and junior project manager and requires strong communication skills, multitasking, and a proactive approach to problem solving.
The primary objective of this position is to ensure the smooth running of projects by coordinating teams, monitoring deadlines, maintaining documentation, and supporting communication with clients and stakeholders.

Key Responsibilities:
- Assist in planning and tracking project progress to ensure adherence to deadlines and key milestones.

- Communicating complex information in a clear and understandable manner.

- Communicating and collaborating with internal and external teams to ensure completion of tasks and alignment with project objectives.

- Monitoring data quality and promptly escalating risks or issues that may impact scope, timelines, or quality.

- Providing regular project updates to clients and stakeholders, aligning expectations, and ensuring transparency.

- Maintaining and updating key project documentation: budget reports, trackers, meeting minutes, delivery schedules.

- Monitoring production KPIs (speed, quality), conducting random quality checks to maintain consistent results.

- Identifying and escalating scope changes at client request to the appropriate internal teams.

- Organizing and conducting meetings with the team/clients to agree on goals, discuss issues, and discuss project status.

- Assisting in resolving project issues and optimizing work processes to improve efficiency.

Requirements:

- Higher education in business, IT, or a related field (preferred)
- Experience in project coordination, operations, or support
- Understanding of the project lifecycle and basic Project Management principles
- Excellent planning, organization, and multitasking skills
- Strong communication skills, ability to clearly communicate information
- Ability to handle risks and problems, results-oriented
- Experience with project management tools (JIRA, Trello, Asana)
- Skills in working with spreadsheets, reports, and calculations
- Mandatory language requirements

Fluency in English and Russian/Ukrainian (oral and written)
will be an advantage

• Experience in data annotation or markup;
• Understanding of Agile/Scrum, Kanban;
• Experience working with cross-functional teams;
• Basic knowledge of IT processes and software development.
   

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.

Now we are looking for a Software Development Engineer (MLOps) to join us as part of our team.

About the role

As a Senior ML Operations Engineer, you will support teams building and deploying AI-driven solutions, helping them overcome common challenges in the ML development, deployment, and support lifecycle. This role offers autonomy in decision-making, encouraging a proactive approach to solving complex issues and finding optimal solutions for scalable systems.

About the project

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. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more.

Team composition

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.
• Provide mentorship, technical guidance, and perform code reviews for team members.
• Design and deliver on projects end-to-end with little to no guidance.
• 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.
• Contribute to strategic planning in a way that ensures the team is building exceptional products that bring real business value.
• 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 equivalent practical experience).
• 5+ years of hands-on software development experience with Python (Java experience with strong Python proficiency also considered).
• 4+ years of experience designing and building distributed software systems and architectures.
• 3+ years of hands-on experience deploying and operating Machine Learning services in production.
• Experience supporting ML lifecycle operations including post-deployment monitoring and maintenance.
• Experience in cloud-native stack, with a practical understanding of containerization technologies such as Kubernetes and Docker.
• Demonstrated experience with SQL and NoSQL database design and implementation.
• Ability to decompose complex problems into iterative, well-defined solutions.
• Strong problem-solving abilities with focus on building scalable, efficient, and maintainable systems.
• 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.

Interview Process

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)
5. Final Client Interview (60 min)

About the Role

We are looking for a strong engineer who can help us build AI-powered tools and automation for real business problems.

We work with large amounts of business data and are building internal systems for verification, enrichment, and automation. We need someone who can quickly understand a problem, suggest a practical solution, and build it.

This role is very hands-on. We are looking for a builder — someone who likes solving problems, moving fast, and turning ideas into working products.

What You’ll Do

• Build AI agents and automation workflows
• Work with LLMs (OpenAI, Claude, etc.)
• Build tools that help automate manual work
• Integrate APIs and external systems
• Improve speed, quality, and reliability of workflows
• Quickly test ideas and move them into production
• Work closely with business and product teams

What We’re Looking For

Must Have

• Strong Python skills
• Experience building real products, systems, or automation
• Experience working with LLMs and AI tools
• Experience with APIs and integrations
• Ability to solve problems independently
• Fast execution and ownership mindset

Strong Plus

• Deep experience with AI-native development workflows
• Daily use of Claude Code, Codex, Cursor, or similar agentic coding tools
• Experience building products using AI-assisted engineering environments

Nice to Have

• Experience with LangGraph, CrewAI, AutoGen, or similar frameworks
• Experience with RAG, vector databases, or AI memory systems
• GitHub or personal projects
• Experience working with large amounts of data

Important

We are not looking for someone who only builds no-code automations.

We are looking for someone who can understand a business problem, think through the solution, and build working systems.

Please share examples of projects you built and your GitHub (if available).

We Offer

• Remote work
• Long-term collaboration
• High-impact projects
• Modern AI tools and technologies
• Fast-moving environment

We are looking for an AI Application Engineer to build AI-enabled applications, internal tools, and agentic workflows using modern AI coding and development platforms such as Codex, Claude Code, ChatGPT, Claude, Vercel, and related APIs/SDKs. This person will be responsible for turning business needs into working software quickly. They will use AI-native development tools to accelerate prototyping and production delivery, while still applying strong software engineering judgment around architecture, security, testing, maintainability, and user experience. This is not a research role and not a pure prompt-engineering role. It is a hands-on builder role for someone who can design, build, test, deploy, and iterate on AI-powered applications and agents.

The position requires 3-4 hours of overlap with the Pacific time zone.

Key Responsibilities:

• Build AI-powered web applications, internal tools, prototypes, and workflow automations using modern full-stack technologies.
• Develop and configure agents in platforms such as ChatGPT, Claude, and related enterprise AI environments.
• Use AI coding tools such as Codex, Claude Code, Cursor, GitHub Copilot, or similar tools to accelerate software development while maintaining quality standards.
• Build applications using frameworks and platforms such as Next.js, React, TypeScript, Node.js, Python, Vercel, APIs, databases, and cloud services.
• Integrate large language models into applications using APIs, SDKs, tool calling, function calling, retrieval, memory, structured outputs, and workflow orchestration.
• Translate business requirements into working software, including lightweight product discovery, technical design, prototyping, testing, deployment, and iteration.
• Evaluate where an AI agent, chatbot, workflow automation, or traditional application is the right solution.
• Create reusable templates, components, agent patterns, and development practices that help teams build faster.
• Partner with business stakeholders, product managers, designers, engineers, data teams, security, and legal/compliance partners as needed.
• Ensure applications and agents are secure, reliable, explainable enough for the use case, and aligned with company standards.
• Measure adoption, usability, quality, and business impact of AI-enabled solutions.

Required Qualifications:

• 7+ years of software engineering experience, preferably in full-stack, product engineering, internal tools, platform engineering, or automation roles.
• Strong proficiency in TypeScript/JavaScript, especially React, Next.js, Node.js, APIs, and modern frontend/backend development.
• Working knowledge of Python for scripting, automation, API integrations, data handling, or agent workflows.
• Experience building and deploying web applications using platforms such as Vercel, AWS, GCP, Azure, or similar cloud/deployment environments.
• Hands-on experience with generative AI tools such as ChatGPT, Claude, Codex, Claude Code, Cursor, GitHub Copilot, or similar AI development tools.
• Experience integrating LLMs into applications using APIs, SDKs, prompt patterns, structured outputs, retrieval, tool calling, or workflow automation.
• Strong software engineering fundamentals: clean code, testing, Git, code review, debugging, logging, documentation, security awareness, and maintainability.
• Ability to work directly with non-technical stakeholders and turn ambiguous business problems into working solutions.
• Strong judgment about when to use AI, when not to use AI, and how to keep a human in the loop for higher-risk workflows.

Preferred Qualifications:

• Experience building AI agents, custom GPTs, Claude projects, workflow agents, copilots, or enterprise AI assistants.
• Experience with Vercel AI SDK, LangChain, LlamaIndex, Semantic Kernel, OpenAI APIs, Anthropic APIs, or similar frameworks.
• Experience with retrieval-augmented generation, vector databases, embeddings, search, knowledge bases, and enterprise data integrations.
• Experience building internal productivity tools, employee-facing workflows, operations tools, or business process automation.
• Experience with authentication, permissions, secure data handling, audit logging, and enterprise deployment patterns.
• Experience designing lightweight user experiences for AI tools, including chat interfaces, agent dashboards, task flows, and approval workflows.
• Comfortable working in fast-moving, prototype-to-production environments.

Project Description

This team is working with an AI chip company that develops specialized software-centric Machine Learning Systems-on-Chip (MLSoC) to enable high-performance, power-efficient "Physical AI" at the edge. Their technology is designed for robotics, autonomous vehicles, and smart cameras, allowing them to process complex computer vision and multimodal AI tasks locally with very low power consumption.

Job Description
The ideal candidate is an ML engineer with a strong background in autonomous systems and mobile robotics. The role requires someone who has spent meaningful time training ML models for complex autonomous platforms—focusing on perception, navigation, and control in GPS-denied, high-speed, and visually complex environments.

The candidate must have hands-on production experience with NVIDIA Isaac Sim and the Omniverse ecosystem, including building photorealistic simulation environments, running Omniverse Replicator synthetic data pipelines for perception, and closing the sim-to-real gap on real robotic hardware. Experience with reinforcement learning or imitation learning for navigation policies is required—specifically training agile navigation policies in simulation and validating them on hardware. A background from an autonomous robotics company, a research group, or an embodied AI team is a must.

On the ML side, the candidate will own the full perception model pipeline: training and fine-tuning visual-inertial odometry components, stereo depth estimation, and defect detection models on synthetic sensor data generated in Isaac Sim; quantizing those models to INT8/BF16 for deployment on the customer MLA; and profiling MLA utilization across navigation, inspection, and complex tracking use cases. The candidate will be the first to apply the custom Palette toolchain to a robotics AI stack—a genuinely novel workload requiring comfort navigating a custom MLA compiler with limited prior art. Strong PyTorch proficiency, familiarity with autonomous control stack integration, and a demonstrated track record of deploying perception models on real-world hardware are essential.

Job Responsibilities

We are seeking an exceptional Senior/Principal Engineer, Robotics Software to join our cutting-edge Robotics and AI software team. The ideal candidate brings deep, hands-on experience in autonomous mobile robots (AMRs), aerial robots. 

• Drive technical discussions relating to architecture, design, and development of software and hardware systems for AMRs, and/or humanoid robots.
• Build and deploy perception, localization, and navigation systems using Lidar-based and Visual SLAM techniques.
• Integrate deep learning models for object detection, motion planning, behavior prediction, and scene understanding.
• Contribute to or lead R&D efforts related to Generative AI and its applications in robotics.
• Collaborate with cross-functional teams including electrical engineers and AI scientists to deliver complete solutions.
• Mentor junior engineers and provide strategic input into long-term robotics and AI vision.

We are an international developer of IT products for medicine and related services. Our products are used by more than 5,000 doctors and more than 1,000 clinics in Europe.

The goal is to attract the largest possible audience to the main projects - clinics and doctors up to 3 million. As well as expanding unique traffic to 10 million per day until 2025. We are looking for AI Engineer / AI Architect with deep knowledge of Fundamental Mathematics, Probability Theory and Bayesian Statistics, Graph Algorithms, Mathematics of Transformers, Hybrid AI Approaches, Uncertainty Assessment.

Must-have skills are:
1. ML and Data Science (Core):
- Expert in NLP & LLM: Deep understanding of Transformers architecture (BERT, RoBERTa, GPT, T5, Llama/Mistral). Experience with Large Language Models (LLM) – not prompt engineering, but fine-tuning (PEFT, LoRA) of open-source models on specific datasets.
- RAG (Retrieval-Augmented Generation): Experience building RAG systems is required. The AI ​​must be able to search for information in different data sources.
- Named Entity Recognition (NER) & Information Extraction: Ability to extract specific entities from unstructured text.
- Tabular Data & Classic ML: Confident use of classical algorithms (XGBoost, CatBoost, LightGBM) for analyzing structured data and building probability scoring models.
- Frameworks: PyTorch (preferred) or TensorFlow/Keras. Proficiency in HuggingFace, Scikit-learn, Pandas, and NumPy.

2. MLOps:
- Experience wrapping models in APIs (FastAPI, Flask) with minimal latency. 

- Docker knowledge and experience working with local GPU instances are required.
- Experience working with vector databases (Pinecone, Milvus, Qdrant, ChromaDB) for quickly searching for similar cases or working with knowledge bases.

- ML Pipelines: Experience building model training and retraining pipelines (Airflow, MLflow, DVC).

3. MedTech and Security:
- Practical working experience with sensitive personal data and GDPR/DSGVO requirements.

- It is important to be able to deploy and optimize local models (Llama 3, Mistral, Mixtral) within a closed company environment to ensure data privacy.
- Skills in quantization and distillation of models to speed up work without significant loss of quality.

Nice-to-have skills:
- Experience working specifically with medical data (EHR, EMR; HL7, FHIR, ICD-10/11 standards). 

- Knowledge of Interpretability/Explainable AI (XAI) methods. The end user should understand why the AI ​​suggested a particular option (SHAP, LIME).

- Experience with multimodal models.

What we offer:
- Paid holiday for 28 working days.
- Transparent incentive system.

Working with us means:
- Unique technological and innovative projects.
- Gaining experience in modern western world practices in security, scalable architecture, etc.
- In-depth knowledge of telemedicine.
- Working with Big data, high load, distributed computing and data buses.
- Socially important projects.
- Opportunity to influence both technology and product solutions.
- Profitability and stability of a large European company.

🔹 100% remote | 🌎 Global team | ⏳ Full-time

NineTwoThree AI Studio is a premier product design, engineering, and marketing firm specializing in custom AI, web, and mobile applications for established brands and funded startups. We are based in Massachusetts but with an American and European staff and a strong, collaborative remote culture.

We’re a team that loves doing good work with great people. Our relatively small size keeps us fast and nimble. The wealth of knowledge, experience and talent paired with proven recipes and best practices allows us to find opportunities to help new products succeed.

With a portfolio of over 150 launched products over 13 years, NineTwoThree has garnered recognition as a top AI agency in the U.S., earning accolades such as inclusion in the Inc. 5000 list for four consecutive years and being named among the top 50 AI firms alongside industry leaders like Microsoft, NVIDIA, and IBM. We’ve built AI and ML tech for big brands like Consumer Reports, FanDuel, and Nara, as well as startups in legal tech, logistics, education, and more. 

Role Overview

As an ML Engineer at NineTwoThree AI Studio, you will sit at the intersection of production-grade software engineering, advanced natural language processing, and client delivery. We build custom, high-impact AI systems for brands and startups across diverse industries (such as healthcare, logistics, and fintech).

Instead of siloed academic research, this role demands a product-minded builder. You will design, optimize, and deploy robust LLM applications, custom predictive analytics, and agentic workflows directly into our clients' software ecosystems, taking absolute ownership of features from prototype to production.

Technology Stack

• Core Frameworks & Arch: Transformer models, modern LLM APIs (Anthropic Claude, OpenAI, AWS Bedrock, etc.), Open-Source LLMs.
• Orchestration & Agentic Design: Experience designing LLM workflows, agentic systems, or retrieval pipelines using frameworks such as Langchain, LangGraph, LlamaIndex, or equivalent approaches.
• Data & Search: Vector databases (Pinecone, pgvector, Milvus, Qdrant, etc.), SQL, and data engineering pipelines.
• Traditional ML: Supervised and Unsupervised learning (Classification, Regression, Anomaly Detection).
• Cloud & Infrastructure: AWS (Lambda, SageMaker, Bedrock, EC2) and modern DevOps/retraining pipelines.
• Languages: Production-grade Python.

Responsibilities

• Architect & Build AI Features: Design and implement robust classical ML and generative AI solutions, striking the right balance between autonomous agentic architectures and deterministic pipelines.
• Evaluate: Design and maintain evaluation frameworks to measure AI quality, reliability, safety, and business impact before and after deployment.
• Integrate & Deploy: Partner closely with full-stack developers and DevOps to seamlessly integrate AI capabilities into client web and mobile applications using serverless architecture (e.g., AWS Lambda) or API endpoints.
• Optimize for Production: Refine prompts, system instructions, and chunking strategies to balance accuracy, latency, token consumption, and data privacy.
• Traditional Predictive Analytics: Clean and process unstructured or historical client data to train/fine-tune custom algorithms for specific business problems (such as forecasting, classification, or anomaly detection).
• Collaborate & Communicate: Actively participate in client discovery sessions, translate ambiguous business requirements into viable technical scopes, and demo prototypes directly to stakeholder teams.
• Maintain Engineering Excellence: Engage in constructive code reviews, implement rigorous validation patterns to test AI outputs, and contribute templates or runbooks to our internal AI knowledge base.

Technical Experience

• Proven Track Record: 3+ years of experience engineering software with a strong focus on machine learning and natural language processing.
• LLM & Generative AI Mastery: In-depth understanding of modern LLM architectures, context window mechanics, semantic search techniques, and the limitations of generative systems. Ability to identify when a deterministic solution is preferable to an LLM or agent-based solution.
• Production experience: Experience building and operating production AI systems, including monitoring, evaluation, debugging, and iterative improvement.
• Evaluation experience: Understanding of evaluation methodologies for LLM-based systems, including retrieval quality, hallucination detection, and task-specific performance measurement. Ability to reason about tradeoffs between quality, latency, cost, reliability, and engineering complexity.
• Python & SQL Proficiency: Exceptional Python coding skills and the ability to query, clean, and structure data efficiently.
• Cloud Infrastructure: Hands-on experience deploying ML or API services within cloud ecosystems, preferably AWS.
• Ownership: Comfortable taking ownership of ambiguous problems from initial discovery through production deployment and ongoing support.

Product & Team Capabilities

• Ambiguity to Execution: Ability to drop into a completely new industry vertical, understand its data constraints, and spin up a working proof-of-concept within a few weeks.
• The "Product Engineer" Mindset: Passion for seeing things ship and understanding why something is being built from a business value standpoint, not just what is being built.
• Communication: Fluent written and spoken English. Comfortable interacting with client stakeholders and breaking down technical workflows into clear concepts.
• Adaptability: Eagerness to experiment with and evaluate fast-emerging AI development tools, models, and frameworks.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).

What We Offer

• Annual paid vacation: 20 days off per year during the first 3 years, increasing to 25 days in later years
• Paid sick leave, 10 national holidays, and 2 company days off
• Well-being budget
• Global health coverage 
• Maternity/paternity leave
• Reimbursement of expenses for professional development courses and certifications (up to 100% in agreement with Manager)
• Strong positive engineering culture, a tightly-knit team of professionals with a good sense of humor

What's The Process

We value your time and ours and make the process fast and easy. Our interview process takes the following steps: a short interview with the HR, 2nd technical interview with ML Engineer and CTO (optional), 3rd live-coding interview, Offer.

Location: London, UK (relocation is expected)

Employment: Full-time
 

We are looking for a Founding Engineer to join an early-stage AI startup building automation solutions for the Testing, Inspection, Certification, and Compliance (TICC) industry.
 

As one of the first technical hires, you will work directly with the CTO, helping to build the company's core AI platform while working closely with customers to automate real operational workflows.
 

Responsibilities:

• Design, develop, and deploy end-to-end software solutions.
• Work directly with customers to understand their business processes and identify automation opportunities.
• Build AI-powered solutions using LLMs, computer vision, workflow automation, and integrations with third-party systems.
• Develop features from idea to production with a strong focus on business impact.
• Integrate with legacy software, sensors, laboratory equipment, and external APIs.
• Contribute to the architecture of the core platform.
• Help shape engineering processes and grow the engineering team as the company scales.
   

Requirements:

• Strong software engineering background with the ability to work across different technologies and tech stacks.
• Experience building and shipping production software independently.
• Product mindset with the ability to solve business problems through technology.
• Excellent communication skills and ability to work directly with customers.
• Comfortable taking ownership and working in a fast-paced startup environment.
• Willingness to travel across the UK (2–3 days per week during customer onboarding phases).
   

Nice to Have:

• Production experience with AI/ML (LLMs, AI agents, Computer Vision, Data Science).
• Experience with cloud platforms (preferably GCP).
• Previous startup or Founding Engineer experience.
• Experience migrating legacy systems.
• Consulting or Forward-Deployed Engineering background.
• Experience in compliance, inspection, logistics, facilities management, or industrial software.
• Experience working with non-technical stakeholders.

We are looking for a Senior AI/ML Engineer to join a distributed AI team and build production-ready solutions focused on document processing, automation, and business applications. This role covers the full lifecycle of Generative AI systems, from concept to deployment, with a focus on scalable architectures, real-world performance, and measurable outcomes.

Required for this role

• 5+ years of experience in hands-on AI/ML engineering, delivering production-grade systems
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, Mathematics, or related field
• Proven track record of building, deploying, and maintaining AI/ML solutions in production environments with measurable impact
• Strong proficiency in Python and relevant AI/ML libraries
• Practical experience delivering end-to-end Generative AI solutions, including production use of LLMs, model fine-tuning, and prompt engineering
• Experience building document processing pipelines and evaluating outputs using structured metrics and feedback loops
• Ability to design scalable, high-performance AI systems, balancing cost, latency, and quality
• Working knowledge of Git and agile delivery practices
• Strong problem-solving skills, attention to detail, and ability to work independently within distributed teams

Nice to have

• Experience with LLM orchestration frameworks such as LangChain
• Knowledge of MLOps practices, including CI/CD, monitoring, and model lifecycle management
• Experience with vector databases, embeddings, and retrieval-augmented generation (RAG)
• Familiarity with document intelligence, OCR, or structured data extraction, and experience delivering AI solutions in enterprise or client-facing environments

Your responsibilities

• Design, develop, and deploy production-ready AI solutions with a focus on Generative AI and LLM-based applications
• Build and optimize document extraction and processing pipelines powered by LLMs
• Develop and refine prompt engineering strategies to improve output accuracy and consistency
• Analyse and optimize AI workflows across cost, latency, and quality trade-offs
• Develop, test, and enhance features within AI systems to meet evolving business needs
• Support the full lifecycle of solutions, from prototyping to deployment and monitoring
• Collaborate with stakeholders to align technical solutions with business goals and communicate complex concepts clearly
• Monitor and evaluate model performance in production, driving continuous improvements
• Stay up to date with advancements in Generative AI and apply new approaches where relevant

What you get

Your time off

• 18 paid vacation days and 10 paid sick days annually
• 10 Ukrainian public holidays
• Maternity and paternity leaves
• Marriage and Parenthood Package
• Additional leave for major life events
• Sabbatical leave opportunities

Learning & growth

• Sombra University workshops and internal learning programs
• Tech Communities and knowledge sharing sessions
• Language courses and workshops
• Mentorship opportunities

Health & well-being

• Sports compensation or health insurance coverage
• Participation in races and marathons
• Corporate doctor (telemedicine)
• Well-being initiatives and workshops

And even more

• Company-provided technical equipment
• PE administration and tax support
• Internal referral program
• IT Club loyalty program
• Company events and volunteering initiatives

Before you apply

Our recruitment team will carefully review your profile, and if we see a good match with the role, we’ll reach out to you shortly.

If you don’t hear from us within 5 business days, it means we’ve decided to continue the process with other candidates for this position. Thanks for understanding.

We are looking for an AI/ML Research Scientist.

Requirements:

• PhD with 1+ years of research experience in Electrical Engineering, Computer Science, Information Systems, or a STEM-related field
• 1+ years of experience with modern machine learning architectures including Transformers, Graph Neural Networks, and Diffusion models
• Strong coding skills in Python and C++
• Experience with machine learning frameworks like PyTorch
• At least 1 publication in top machine learning conferences (NeurIPS, ICML, ICLR, etc.)
• Experience with deep learning on graphs (general graphs, circuit graphs, molecular graphs, or trees)
• Familiarity with classical search and optimization techniques (Genetic Algorithms, Monte-Carlo Tree Search, Dijkstra's Algorithm, etc.)
• Experience with EDA tools, either commercial or open-source
• Publications in top-tier venues focusing on AI for chip design or AI for materials science. 

We are looking for a Middle AI Engineer who will help us build, integrate, and scale AI-powered products that solve real business challenges.

This role is focused on creating production-ready AI solutions — from backend services and LLM integrations to RAG systems, AI agents, and workflow automation. You will work closely with Product Managers, developers, and business teams to transform ideas into reliable AI products that deliver measurable value.

What you will do:

• Develop production-ready AI services, backend components, APIs, and integrations for internal and external AI products.
• Design and implement AI solutions based on Large Language Models (LLMs), RAG architectures, AI agents, and workflow automation.
• Build and optimize Python-based services and backend infrastructure with a focus on scalability, reliability, and maintainability.
• Integrate and work with different types of AI models — including proprietary APIs (OpenAI, Anthropic, Gemini, etc.) and locally hosted models.
• Design and improve RAG pipelines: data processing, embeddings, vector search, retrieval optimization, knowledge bases, and AI response quality improvement.
• Develop AI agent systems and automation workflows, including integrations with external APIs, corporate systems, and internal tools.
• Conduct technical experiments with models, prompts, architectures, and inference parameters to identify the most effective solutions.
• Implement AI quality evaluation and monitoring approaches: analyze model performance, improve reliability, reduce errors, and optimize system efficiency.
• Collaborate with Product Managers and cross-functional teams to translate product requirements into technical solutions and scalable architectures.

• Ensure AI services are secure, stable, and production-ready by monitoring performance, resolving issues, and continuously improving systems.

   

What we expect from you

• 3+ years of commercial software development experience with strong Python expertise.
• Experience building backend services, APIs, and integrations using modern technologies.
• Strong understanding of software engineering principles: clean code, architecture patterns, testing, scalability, and maintainable solutions.
• Practical experience developing AI products based on Large Language Models (LLMs).
• Hands-on experience with RAG systems, embeddings, vector databases, retrieval optimization, and AI application development.
• Experience working with AI model integrations, including external APIs and/or locally deployed models.
• Understanding of AI agents, workflow automation, and approaches to building reliable AI systems.
• Experience with Docker, CI/CD, and production deployment processes.
• Ability to analyze AI system performance and improve quality, efficiency, and reliability.
• Upper-Intermediate English level (B2+) 

Will be a plus:

• Experience with fine-tuning or adapting AI models.
• Experience with MLOps / LLMOps practices.
• Knowledge of NLP approaches.
• Experience with cloud platforms and scalable infrastructure.

What we offer

• Competitive compensation up to $4,000, depending on your experience and expertise.
• Office-based work in Lviv with the possibility of a hybrid schedule.
• High level of technical ownership and the opportunity to solve challenging engineering problems.
• Professional development opportunities: company-sponsored courses, training, and access to necessary tools and resources.
• A team of experienced specialists who value expertise, initiative, and high-quality engineering.
• The opportunity to become one of the key engineers shaping the company’s AI direction.
• Relocation support for candidates from other cities, including assistance with moving and adaptation in Lviv.

Our client is the leader in the Early Childhood Education (ECE) sector, providing the most widely used developmental assessment and curriculum system in the US. 

They are early in shaping how AI changes the way they build and operate software. They have active initiatives in AI tooling cost-management and agentic development workflows, but their direction is still forming and will keep evolving as the field does. 

They are not looking for someone to execute a fixed plan, they are looking for an experienced practitioner who can validate the direction we are setting, bring expertise we do not have in-house, stay ahead of what is emerging, and help us adjust and grow as the landscape shifts. This person is hands-on enough to build and prove things directly, and senior enough that we trust their judgment on where to place bets.

What you will do

• Act as a hands-on technical partner across AI engineering initiatives, currently spanning tooling cost management, model routing and selection, and agentic development workflows.
• Pressure-test the approaches they are considering, tell them where they are wrong or where a better path exists, and back it with evidence rather than opinion.
• Bring outside expertise and patterns from how other organizations are solving these problems, so they are not learning everything the expensive way.
• Track what is emerging across models, tooling, frameworks, and techniques, and translate it into concrete recommendations on what they should adopt, defer, or ignore.
• Build and run proofs of concept to validate ideas quickly, then help them decide what to operationalize.
• Help mature their agentic development workflow so engineering teams can adopt it, including model routing and token efficiency.
• Partner with Infrastructure and Security so that what they build fits their architecture and meets their data privacy obligations.
• Help them build internal capability, so the expertise compounds with their team and does not leave when the engagement ends.

Required background

• 7+ years in software, platform, or ML engineering, with recent, direct experience building and operating LLM-backed systems in production.
• Demonstrated breadth across the current AI engineering stack: models and their tradeoffs, inference cost dynamics, gateways and routing, agentic workflows, and the AI coding tool landscape.
• A track record of forming a point of view on fast-moving technical decisions and being right often enough to be trusted with them.
• Strong hands-on engineering ability. This person builds, benchmarks, and ships, not just advises.
• Comfort operating with ambiguity and early-stage direction; able to bring structure rather than wait for it.

• Cloud and infrastructure fluency (AWS preferred, including Bedrock).

   

Strongly preferred

• Experience helping an organization adopt AI-first engineering practices, not just individual tool use.
• Hands-on model evaluation and routing design, and exposure to AI cost governance.
• Experience in regulated data environments. 
• A habit of staying current through real practice (building, writing, contributing) rather than headlines.

What this role is not

• Not a fixed-scope implementation seat. The work will change as their direction evolves, and they want someone who helps drive that change.
• Not a data science or model training role. The focus is applied AI engineering, integration, and enablement.
• Not a manager. Individual contributor, hands-on, with influence earned through expertise.

We are looking for a Lead/Senior AI/ML Engineer to join our team!

Our client is an innovative technology division within one of the world's top-10 copper producers. The team focuses on leveraging AI, machine learning, and advanced analytics to optimize industrial operations, improve asset reliability, and support data-driven decision-making across global mining and production facilities. The role is focused on building intelligent solutions for predictive maintenance, anomaly detection, and asset performance optimization, helping reduce downtime and improve operational efficiency across large-scale industrial environments.

Part-time work is also possible (4 hours a day).

Responsibilities:

• Design, develop, and deploy machine learning models for predictive maintenance, anomaly detection, and asset health monitoring.
• Build and maintain production-grade ML pipelines for time-series forecasting and sensor/telemetry data processing.
• Collaborate with Data Engineers and Analytics Engineers on data preparation, feature engineering, and model integration.
• Integrate model outputs, risk scores, and predictive insights into operational dashboards and business applications.
• Establish and maintain MLOps processes, including model deployment, monitoring, retraining, and drift detection.
• Research and evaluate new AI/ML approaches, tools, and technologies to improve predictive capabilities and business outcomes.
• Work closely with business and technical stakeholders to translate complex analytical results into actionable recommendations.

Requirements:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• Strong Python skills and hands-on experience with Pandas, NumPy, Scikit-Learn, SciPy, and related ML libraries.
• Proven experience with time-series forecasting and predictive modeling techniques (ARIMA, Prophet, XGBoost, LSTM/RNN, etc.).
• Experience working with telemetry, IoT, sensor, or equipment performance data.
• Hands-on experience with Azure Machine Learning, Databricks, MLflow, or similar MLOps platforms.
• Strong SQL skills and experience working with both relational and non-relational databases.
• Experience building and deploying production-ready ML solutions.
• Strong analytical and problem-solving skills with the ability to translate technical insights into business value.

Nice to have:

• Master's or PhD degree in Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• Experience in mining, manufacturing, heavy industry, utilities, or other asset-intensive domains.
• Knowledge of Operational Technology (OT) environments and reliability engineering concepts.
• Experience with enterprise asset management systems such as SAP PM or IBM Maximo.
• Familiarity with reliability methodologies such as RCM or FMEA.
• Experience with real-time data processing and anomaly detection on streaming platforms (Kafka, Azure Stream Analytics, etc.).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

About us

DroneOps is a company creating innovative UAV-related products, focused on UAV autonomy and navigation, founded in 2023. We are a team of innovators and inventors who take on the duty to help the armed forces of Ukraine defend our country and democracy by providing reliable advanced systems that simplify their work, improve personnel safety, and enable more cost-effective and precise UAV mission execution.

Overview

We are looking for a Middle / Senior Computer Vision / Deep Learning Engineer to extend our onboard navigation capabilities with modern perception and learning-based methods.

This is a hands-on R&D role: you work from research and prototypes to production on edge hardware, collaborate with software, and flight teams, and help shape how new CV/DL features are built and shipped. The role suits someone who can follow state-of-the-art work, implement what fits our constraints, and care about real-world performance—not only offline benchmarks.

Responsibilities

Relocalization & navigation

• Design and develop satellite, map, and semantic navigation capabilities that improve the overall quality of our navigation
• Build and maintain pipelines for map and reference-data preparation before missions
• Extend the existing visual-inertial navigation stack with relocalization and map-based aiding features
• Develop training pipelines for these tasks (data preparation, training, evaluation, and iteration)
• Create utilities that make map preloading and mission setup convenient for operators and integrators
•  

Research & implementation

• Track relevant research and industry approaches; prototype and adopt methods where they clearly improve the product
• Reimplement or adapt algorithms when off-the-shelf solutions do not fit our data, hardware, or latency requirements
• Define evaluation metrics and acceptance criteria for new features before field and deployment rollouts
•  

Edge deployment & production

• Optimize models and inference for target onboard hardware
• Integrate new features into the production codebase with stable APIs, logging, and failure handling
• Take part in architecture decisions, code review, and team practices that keep production quality high as the stack grows
•  

Required skills & experience

• 3+ years of practical experience in computer vision and deep learning
• Strong Python; ability to write clear, maintainable code for experiments and production paths
• Experience with training and deploying deep learning models (PyTorch)
• Familiarity with model optimization for edge or embedded devices (pruning, quantization, ONNX/TensorRT-class tooling, or equivalent)
• Comfort working with geospatial or map-related data and preprocessing pipelines
• Practical production mindset: reproducible experiments, versioning, and validation on real data
• English B2+ for documentation and technical discussion; Ukrainian for day-to-day team communication
•  

Nice to have

• Experience with deep learning keypoint detection and matching approaches
• Comfortable with geometric computer vision (camera models, epipolar geometry, robust estimation)
• Multi-sensor fusion / SLAM / EKF background
• UAV, robotics, or aerospace field experience
• Experience with satellite or aerial imagery, semantic segmentation, or visual place recognition
•  

What we offer

• Competitive salary
• Reservation from mobilization
• Impact on improving our country's defense capabilities
• 21 days of vacation + public holidays, sick leaves

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.
 

     You'll be a great fit if you have:

•  Strong Python Experience (2 year +);
• Experience with LLM , Diffusion models;
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;

• Strong experience in statistics;

  What you'll do:

• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

     We ensure your growth with:

• Competitive salary fixed in USD
• Flexible working schedule and fully remote work format
• Paid vacation days and sick leave days 
• Personal and professional development opportunities
• Participation in building innovative projects from scratch using modern technologies
• Team-building activities and corporate events
• English classes and educational events.