Jobs ML / AI Engineer

We are looking for a hands-on Agentic Deployment Expert who will drive AI adoption across the entire company, deploy specialized AI agents into real workflows, and maintain the infrastructure behind them.

This role is for someone who moves fast, thinks in systems, and knows how to turn AI tools into real business leverage. You will need to understand where AI can replace brute-force manual work, and deploy practical solutions across departments. You will not just experiment with AI — you will make it operational.

What you will do

• Drive AI adoption across all major company departments
• Identify repetitive, manual, and low-leverage workflows that should be replaced or improved with AI
• Deploy and improve specialized AI agents for different business functions, including one dedicated to external communications
• Build and maintain internal AI tooling and the infrastructure behind it
• Work hands-on with Docker, Telegram bots, cloud environments, and AI products
• Monitor new AI releases, models, and tools continuously, and decide what is worth testing and deploying
• Optimize infrastructure costs while keeping systems scalable and reliable
• Maintain strong security standards, including encryption and safe AI stack usage
• Help shape and maintain an AI-first internal operating model

What we are looking for

• Mid or Senior-level specialist
• Strong hands-on experience with AI tools, agentic workflows, or automation
• Strong practical development skills
• Solid experience with Docker
• Experience building or supporting Telegram bots
• Good understanding of cloud infrastructure
• Strong execution speed and ownership
• Ability to understand business processes deeply and translate them into AI-powered systems
• Strong interest in the fast-moving AI ecosystem
• Someone who does not just talk about AI, but deploys it quickly and effectively to solve real business problems
  
  Would be a plus
• Experience in fintech or other fast-moving product environments
• Experience optimizing infrastructure costs
• Experience with security and encryption best practices
• Experience deploying AI solutions across multiple business functions
• Experience working in startup environments with high autonomy and fast iteration
  
  What we offer
• Opportunity to become the architect of AI adoption across the company
• Real ownership and high-impact work
• Fast-moving AI-first environment
• Fully remote format 
• Full-time cooperation
   

Before scheduling the interview, we will ask for:

2–3 past relevant case studies involving complex AI deployments

This is not a coding role. This is a systems-of-systems role. 

If you build things with AI, this posting isn't for you. 

If you build the systems that govern how AI builds things — keep reading.

What This Role Is

LifeChef is a HIPAA-compliant healthcare platform delivering Medically Tailored Meals. Our engineering team builds on a methodology called Enso — a spec-driven, AI-augmented development framework where every feature starts with a specification, gets built with AI assistance, and is validated against defined criteria.

Enso v1 is linear: spec → generate → validate → ship. It works. But it's hitting scaling limits — the document graph grows with every feature, validation complexity compounds, and the process requires increasing human oversight to maintain quality. This is a familiar problem in any AI-assisted workflow that outgrows its initial architecture.

We need someone to take Enso from v1 to v2: a true agentic system where specialized AI agents handle research, specification validation, code generation oversight, quality assurance, and deviation detection — with structured autonomy, clear escalation paths, and human-in-the-loop at defined decision points, not everywhere.

You would partner directly with the CTO (who designed the current methodology and has strong opinions about where it needs to go) to architect, build, and maintain this system. The first 30 days are heavy collaboration — translating vision into working architecture. After that, you own the evolution of the process while the CTO focuses on product and team.

What You'd Actually Build and Maintain

• Agent topology for the development lifecycle: research agents, spec validation agents, code review agents, compliance checking agents, red-team/adversarial agents — each with defined boundaries, confidence thresholds, and escalation triggers
• Spec-to-code reconciliation system: agents that validate whether implemented code actually satisfies the specification, flagging deviations and ambiguities rather than silently passing
• Multi-model orchestration strategy: routing different tasks to different models based on cost, capability, and risk (expensive models for reasoning, cheap models for classification, open-source where it fits)
• Structured output validation: ensuring agent outputs are parseable, auditable, and actionable — not just "LLM said it's fine"
• Governance and escalation framework: what agents decide autonomously vs. what requires human sign-off, circuit breakers for low-confidence situations, audit logging for compliance
• Evolution engine: the system should improve itself — tracking where agents fail, where human overrides happen, and feeding that back into prompt refinement and architecture changes
• Integration with existing CI/CD: the agentic layer hooks into GitHub Actions, automated testing (Vitest), PHI scanning, secret detection, and compliance validation already in the pipeline

This is infrastructure that the development team operates within. You're not shipping product features — you're shipping the machine that makes product development faster, safer, and more consistent.

What We Need From You

Hard requirements:

• You have designed or built at least one agentic system where AI agents operate with structured autonomy — multi-step workflows with validation, error handling, and escalation. Not just API wrappers. Not just chatbots.
• You understand agent topology as a design problem: which agents need to exist, what their boundaries are, how they communicate, how you prevent cascading failures.
• You have hands-on experience with LLM orchestration frameworks (LangChain, CrewAI, AutoGen, custom implementations — the specific tool matters less than the depth of understanding).
• You think in terms of eval frameworks and validation: how do you know if an agent's output is good? How do you measure drift? How do you build confidence scoring that's actually useful?
• You understand multi-model strategies: when to use which model, cost/capability tradeoffs, how to tier your model usage so you're not burning expensive tokens on classification tasks.
• You can work in both Python and TypeScript, or at minimum are comfortable in one and willing to operate in the other. Our product stack is TypeScript-first but agentic tooling often lives in Python.
• Strong written communication. This role involves heavy async documentation of architectural decisions, process design, and system behavior.

What sets you apart:

• Experience with Model Context Protocol (MCP) — building custom MCP servers, tool-use architectures
• Claude Code, Cursor, or similar AI-native development tools as part of your own workflow (you should be using what you're building systems around)
• Experience in healthcare, fintech, or regulated environments where AI outputs must be auditable and compliant
• Understanding of prompt engineering at the systems level — not "write a good prompt" but "design a prompt architecture that's maintainable, versionable, and testable"
• You've thought seriously about adversarial validation — red-team agents, cross-model verification, structured disagreement as a quality signal
• You have opinions about where agentic AI is overhyped and where it genuinely works, and you can defend those opinions with specifics

What we explicitly don't require:

• A portfolio of 50 agentic projects. The field is young. One deep project with real orchestration depth beats ten shallow ones.
• Product development skills. You won't be building UI or shipping user-facing features.
• Healthcare domain expertise. We'll teach you the domain. You teach us the orchestration.

How We Evaluate

1. Screening questions (in your application) — We're looking for specificity and honesty, not keyword density.
2. Architecture conversation with CTO (90 min) — We'll describe our current system, its limitations, and where we want to go. You'll tell us how you'd approach it. This is a two-way design conversation, not a quiz.
3. Small design exercise (async, take-home) — Given a simplified version of our spec validation problem, design an agent topology. We're evaluating how you think about boundaries, failure modes, and escalation — not production-ready code.
4. Trial sprint (60–90 days) — Heavy pairing with CTO in the first 30 days, increasing autonomy after. Defined milestones at 30, 60, and 90 days.

The Team and Context

Small, senior engineering team, primarily Ukraine-based. The CTO (Jay) designed the Enso methodology, has 20+ years of engineering experience across healthcare, threat intelligence, and enterprise platforms, and has built the governance architecture (constitutions, spec-gates, validation layers) that you'd be evolving. He's technical, direct, and has strong opinions — but he's hiring you because he needs a partner in this, not an executor.

The product stack is Next.js 16, React 19, TypeScript, PostgreSQL, AWS serverless (Lambda, CDK, Amplify Gen 2), with Vitest testing, Pino structured logging, and HIPAA compliance enforced in CI. You don't need to know this stack deeply, but you need to understand it well enough to build agentic tooling that integrates with it.

We're building toward autonomous agentic systems for clinical operations — this development process work is the foundation that makes that possible. If the idea of designing the system that governs how an engineering team builds software excites you, this is the role.

How to Apply

Reply with:

• The most complex agentic or LLM orchestration system you've built — what it did, how it was structured, what you learned
• Your honest take on where agentic AI is right now and what's actually hard
• What interests you about building process infrastructure vs. product features

Generic responses get skipped. We know the field is young — we'd rather hear about one deep experience than a list of tools you've touched.

Job Description

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• +5 years of experience in machine learning and NLP, with a focus on developing applications using LLMs.
• Proficiency in programming languages such as Python and frameworks/libraries like TensorFlow, PyTorch, Hugging Face Transformers.
• Experience with cloud services (AWS, Azure, GCP) for deploying ML models and applications.
• Strong understanding of RESTful APIs for integrating chatbot functionalities into different platforms.
• Familiarity with version control tools (e.g., Git) and ML development tools (e.g., Jupyter Notebooks, MLflow).
• Participate in pre-sales activities, including developing ML offering materials and engaging with clients to understand their needs, presenting tailored solutions, and demonstrating the potential impact of our ML technologies.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Preferred (but not mandatory):

• Certifications or advanced training in machine learning, cloud architectures, or similar fields.
• Active participation in relevant tech communities or contributions to open-source projects in the ML/NLP domain.
•  

Job Responsibilities:

• Design and implement chatbot solutions using Large Language Models such as OpenAI GPT API or similar frameworks.
• Collaborate with cross-functional teams to integrate chatbot solutions into existing platforms and workflows.
• Optimize and fine-tune LLMs for performance, accuracy, and user engagement.
• Build and optimized RAG and vectorized databases
• Monitor and evaluate the performance of chatbot applications, identifying areas for improvement and implementing updates.
• Stay up-to-date of developments in AI, machine learning, and NLP to ensure our solutions remain cutting-edge.
• Develop and maintain documentation related to ML models, including model design, deployment details, and performance metrics.
• Work with data engineers to ensure the availability and quality of data for training and fine-tuning models.

• Implement security measures to protect sensitive information processed by chatbots

   

Department/Project Description:

We are seeking a highly skilled and motivated Machine Learning Developer to join our dynamic team, focusing on developing, deploying, and optimizing Large Language Models for chatbot applications. This role involves working on cutting-edge AI technologies to create conversational agents that provide engaging and insightful interactions with users. The ideal candidate will have a strong background in machine learning, Natural Language Processing, and experience in developing LLM-based chatbots.

ML/CV engineer

We’re looking for a passionate Machine Learning / Computer Vision Engineer to join our team.

As a member of our team, you will participate in research & development of solutions in the field of computer vision, document understanding using cutting-edge machine learning approaches. The position will involve different aspects of R&D including initial research, analysis, prototyping and development. By joining our team you’ll be able to affect Ukrainian Deftech area innovations and contribute to important today’s military products.

Responsibilities:

• Research and development of Image Processing algorithms including CV algorithms
• Research and prototyping of detection and tracking algorithms using ML and CV
• Work with data collection and analysis in order to improve efficiency of ML/CV dependent algorithms

Job Qualification:

• 2 years of commercial experience with Python
• Demonstrated hands-on experience with TensorFlow, PyTorch
• Practical Experience with Machine Learning, including designing, training, fine-tuning of ML models, and integrating machine learning systems into production environments related to Computer Vision, Document Understanding
• Experience with Object Tracking area using ML/CV
• Experience with vision transformer, vision encoder-decoder architectures
• Strong analytical and communication skills

Will be a plus:

• Experience in Miltech development
• Experience with code performance optimization
• Master’s or Bachelor’s degree in computer science, math, statistics, or related field
• Experience in C/C++ 

Working Conditions:

• official employment 
• offline work for growing deftech company (remote is also option but mostly offline)
• military exemption

Join us at 3DLOOK, where innovation meets creativity, as we seek a talented Research Engineer to collaborate with our Core Team. Embark on a journey of maintaining, exploring, and refining our body reconstruction pipeline, delving into the intricate world of 3D machine learning.

About us:

3DLOOK is a leading AI-powered technology company, specializing in mobile body scanning and visualization for a diverse set of industries — from apparel manufacturing and retail to digital health & fitness. Certified by IEEE as a standard in mobile body scanning and earned recognition through multiple awards, such as the Digiday Technology Award and RTIH Innovation Award in 2021.

Are you ready to immerse yourself in the realm of cutting-edge technology? Here’s what we’re seeking:

Requirements:

• With over 5 years of hands-on experience nurturing CV/ML projects from conception to fruition, you’ll be our guiding force.
• Your mastery of 3D computer vision and computational geometry is indispensable, a beacon illuminating our path forward.
• A profound understanding of the mathematical underpinnings of machine learning and numerical optimization is paramount.
• Navigate the labyrinth of data structures, data modeling, and software architecture with finesse.
• Craft intricate validation schemes, unraveling the mysteries of machine learning accuracy.
• Your technical prowess shines with Python, PyTorch/Tensorflow, and an arsenal of numerical and scientific packages.
• Track the evolution of experiments with finesse, leaving no stone unturned in the pursuit of excellence.
• Upper-intermediate proficiency in English empowers seamless communication across borders.
• Flexibility and stellar communication skills define your essence, embodying the spirit of a collaborative team player.

Responsibilities:

• Forge ahead with the development of our body reconstruction pipeline, infusing it with novel features and conducting groundbreaking research to elevate accuracy.
• Architect and maintain a framework to decipher the veracity of predicted measurements, sizes, and 3D avatars.
• Embark on projects that illuminate the path to enhanced accuracy, investing resources where they matter most.
• Safeguard the integrity of our ML pipeline testing flow, ensuring the fidelity of the data in use.

What we offer:

• The opportunity to join a team of professionals and bring your most creative ideas to life;
• Participation in the Stock Option Program is granted after 6 months of work in the company, in case of exceptional results;
• You will be entitled to 4 weeks (20 working days) of paid vacation in a year;
• Paid sick leaves (10 days/year with full coverage);
• Flexible working hours;
• Fully remote working environment.

3DLOOK, we don’t just envision the future—we shape it. If you’re ready to redefine boundaries and chart new territories in the realm of 3D ML engineering, we invite you to join us on this exhilarating expedition.

We are looking for an AI/ML Engineer to join our team and work on real client projects across different domains (AI products, SaaS platforms, automation solutions).

This role is a mix of strong technical work and direct client interaction. You will participate in pre-sales, help shape solutions, and build production-ready AI systems.

Requirements:

• 3+ years of experience in AI/ML
• Strong Python skills (NumPy, Pandas, scikit-learn)
• Hands-on experience with NLP / LLM or Computer Vision
• Experience with LLMs (OpenAI, HuggingFace, or self-hosted models)
• Understanding of ML lifecycle (data → training → deployment)
• Experience with APIs, Docker, and cloud (AWS / Azure / GCP)
• Strong understanding of ML algorithms

Nice to have:

• Experience with RAG, vector databases
• Experience with self-hosted LLMs (LLaMA, Mistral, etc.)
• Experience with MLOps (CI/CD, monitoring, pipelines)
• Experience optimizing inference (latency / cost)

What’s important for us:

• Ability to communicate with clients and explain solutions
• Experience in pre-sales or technical discussions is a big plus
• Strong problem-solving and structured thinking
• Ownership and proactive mindset

What you will do:

• Work on AI/ML solutions for client projects
• Participate in pre-sales and solution design
• Build and deploy production-ready models
• Collaborate with engineers and sales team

We offer:

• Remote work
• Long-term collaboration
• Real client projects and impact on decisions
• Opportunity to grow in AI/ML and client-facing roles

appflame — Ukrainian product-driven tech company building world-class products: Hily, Taimi, AdConnect, Mailkeeper, and more.

About us:

• 7 years in the market, 500+ team members, offices in Kyiv, London, Limassol, and a co-working hub in Warsaw.
• In 2025, appflame ranked 5th among the top 50 employers in Ukraine according to Forbes and won the “Best Place for Growth” award.
• Our apps Hily and Taimi are among the top 5 dating apps in the US with over 70 million users. AdConnect and Mailkeeper focus on building proprietary B2B and B2C solutions.

Our mission:

• To put Ukrainian-built products on the global map.

Our goals:

• Break into the global top 5 product companies.
• Become a unicorn.
• Make Ukraine a country where unicorns are born.

We’re looking for bold, driven people who are passionate about building real products and dream of launching and scaling great startups. You bring the ambition — we provide the environment to make it happen.
 

What you’ll do:

• Design and develop an AI-powered productivity analytics platform — from data pipeline architecture to the final analytical product that helps teams make data-driven decisions.
• Build scalable LLM pipelines (Claude, GPT): develop data chunking strategies, implement MapReduce approaches for parallel processing of large datasets, and synthesize results into structured reports and insights.
• Create a meta-workflow system where LLMs generate, test, and deploy automation scripts in an isolated environment — with automatic self-correction loops and production deployment without manual intervention.
• Develop system-level prompt engineering: build and maintain a library of prompt templates for various analytical scenarios — from summaries and profiles to deep performance analysis.
• Build an evaluation framework for AI output quality control: hallucination detection, consistency scoring, regression tests — ensuring the product delivers reliable and reproducible results.
• Scale the platform to new domains and analysis types without linear growth in manual effort — through an architecture that allows adding new modules via configuration, not code.
• Document AI architecture, define automation specs, and present product insights to stakeholders and clients.
   

It’s a match if you have:

• 2+ years of experience working with LLMs in production: prompt engineering, pipeline development, API integration — with at least 1 year of hands-on experience with advanced features (tool use, structured outputs, agents).
• Strong Python skills (async, dataclasses, type hints, API integrations) and a commitment to writing clean, testable, and maintainable code.
• Understanding of MapReduce patterns for LLM processing: ability to choose chunking strategies, organize parallel processing, and aggregate results into a cohesive analytical product.
• Experience building agentic systems: tool use, self-correcting loops, multi-agent workflows — and the judgment to know when an agent works better than a rigid pipeline.
• Proficiency in SQL and experience working with analytical databases.
• English at C1 level — comfortable reading documentation, writing technical specs, and communicating asynchronously.
• Ownership mentality: you take tasks end-to-end, debug production issues independently, and iterate to deliver results without micromanagement.
   

Nice to have:

• Experience with orchestration/automation platforms (Windmill, Dagster, Prefect) — understanding how to build reliable automated workflows.
• Knowledge of RAG architectures, vector databases, and embedding pipelines — ability to build systems that work with large volumes of unstructured data.
• Experience building evaluation systems for LLMs (LangSmith, PromptFoo, or custom solutions) — understanding how to measure and improve AI product quality.
• Familiarity with Databricks / Delta Lake or Snowflake — experience working with modern data platforms.
• Experience working at product-driven tech companies or AI startups where you needed to build and iterate quickly.
• Understanding of product team metrics (DAU, retention, unit economics) and the ability to connect technical decisions to product impact.
   

Preferred tech stack:

Core:

• Languages: Python (primary), SQL
• LLM APIs: Claude API (Anthropic), OpenAI API
• Databases: PostgreSQL, ClickHouse
• Infrastructure: Docker, Git, FastAPI, Pydantic, pytest, asyncio

Nice to have:

• Languages: TypeScript/JavaScript, Bash
• LLM APIs: Google Gemini API
• Orchestration & Automation: Windmill, Dagster, Prefect, Airflow, Temporal
• RAG & Embeddings: LangChain, LlamaIndex, ChromaDB, Pinecone, Weaviate, pgvector,FAISS
• Eval & Observability: LangSmith, PromptFoo, Weights & Biases, Arize AI
• Databases: Redis, MongoDB
• Data Platforms: Databricks, Delta Lake, Snowflake, BigQuery
• Infrastructure: Kubernetes, AWS (Lambda, SQS, S3), GCP
• CI/CD & DevOps: GitLab CI, GitHub Actions, Terraform

Hiring process: recruiter outreach > interview > test task > final interview > job offer.

We are seeking an experienced and talented Lead Machine Learning Engineer

Innovecs is a global digital transformation tech company with a presence in the US, the UK, the EU, Israel, Australia, and Ukraine. Specializing in software solutions, the Innovecs team has experience in Supply Chain, Healthtech, Software & Hightech, and Gaming.
For the fifth year in a row, Innovecs is included in the Inc. 5000 and recognized in IAOP’s ranking of the best global outsourcing service providers. Innovecs is featured in the Global Top 100 Inspiring Workplaces Ranking and won gold at the Employer Brand Management Awards.

Our value to you: 

• Flexible hours and remote-first mode
• Competitive compensation
• Complete Hardware/Software setup – anything you need for work
• Open-door culture, transparent communication, and top management at a handshake distance
• Health insurance, vacation, sick leaves, holidays, paid maternity/paternity leave
• Access to our learning & development center: workshops, webinars, training platform, and edutainment events
• Virtual team buildings and social activities 
          

If you feel like you’re the perfect match for this role, drop us your CV! 

There are no limitations, no barriers when the right people are on your way — apply for the vacancy and succeed with us!

Innovecs is an equal opportunity employer. All hiring decisions are based on professional qualifications, skills, and experience. We are committed to a transparent, merit-based recruitment process that prevents discrimination and ensures equal opportunities for all candidates. Reasonable accommodations are available upon request throughout the recruitment process to support accessibility and inclusion.

Requirements

• BSc degree in Computer Science, Data Science, Statistics, or a related field. A Master's degree is a plus,
• At least 5 years of relevant work experience in machine learning, data science, or a related field,
• At least 1–2 years of experience in a technical leadership, team lead, or mentoring capacity,
• Proficiency in Python and SQL/NoSQL (Cassandra, MongoDB) for quantitative analysis, modeling, and data manipulation,
• Knowledge of cloud technologies such as AWS Sage Maker and MLOps practices and tools (e.g., MLFlow, KubeFlow),
• Knowledge of basic data structures and algorithms and OOP,
• Experience with Big Data Analytics and tools (e.g., Elasticsearch, Spark, Airflow) for data analysis and visualization,
• Familiarity with model deployment, MLOps practices, and the lifecycle of machine learning models,
• Familiarity with model and application monitoring tools (e.g., Evidently.ai, NewRelic),
• Strong communication, leadership, problem-solving, and stakeholder management skills,
• Strong analytical skills and experience working with large volumes of data,
• A strong desire to continuously learn, improve, and stay updated with the latest technologies and trends in AI/ML,

• Upper Intermediate English level, with excellent communication skills to effectively collaborate with both technical and non-technical teams.

   

Responsibilities

• Lead and mentor a team of ML engineers, providing technical direction and supporting team growth,
• Own the end-to-end development and delivery of ML solutions, from problem framing and experimentation to production deployment and monitoring,
• Analyze large, complex data sets to translate them into actionable insights,
• Design and review ML architectures, data pipelines, and MLOps workflows,
• Perform the preparation and preprocessing of both structured and unstructured data to ensure model accuracy and effectiveness,
• Design, develop, implement, and test both descriptive and predictive ML models, focusing on quality, accuracy, and consistency,
• Convert data into meaningful insights and present information using advanced data visualization tools and techniques,
• Deploy models into production environments and be responsible for model management (MLOps),
• Ensure best practices in model development, deployment, observability, CI/CD, and production support.

• Project Description:

  Learning Management and Development enables each member of the company to access various training services, such as trainer-led courses, upskilling programs for Direct and Line Managers, webinars, foreign language lessons, training paths & sets, internship programs, self-learning libraries, external providers (conferences and certifications), and other training services.

   

• Responsibilities:

  • Organization/help any events concerned with training in location;
  • Ability for accurate work in internal management systems and tools;
  • Training modules preparations (infrastructure, materials, invitations, certificates, problem solving etc.);
  • Introduction trainings (consulting, organization, closing in the system).
  • Process the Training plan (assure the accuracy of the forecast);
  • Cooperation with internal and external training providers;

   

• Mandatory Skills Description:

  • Higher education;
  • Good communication skills;
  • Experience with databases;
  • Advanced PC user (MS Office, Outlook, Internet Explorer);
  • Great sense of responsibility with ability to work under pressure independently as well as in teams;
  • Strong attention to details and organization;
  • Self-starter and proactive approach to resolving

#WeAreIn for jobs that impact everyone's life. What if your ideas could change the way the world connects, powers up, or thinks? As a Senior AI/ML Engineer on our Research & Development team, you'll have the opportunity to merge creativity with your technical expertise by shaping the future of technology, driving groundbreaking projects, and bringing new ideas to life. Are you in?

Key responsibilities in your new role

Work on innovative IoT, Industrial, and Automotive technologies in a fast-moving R&D team, turning ideas into real products and patents. 

• Design and develop efficient Neural Network (NN) models with sophisticated architectures for embedded domain, strongly involving application-specific knowledge
• Plan and execute practical experiments to collect/create high-quality datasets
• Combine NN and classic signal processing approaches to make the highly efficient pipelines of problem solving
• Implement the developed solutions under real-world end-user scenarios and requirements and verify its functionality at the Infineon hardware (PSOC, wireless SOCs)
• Help with ML/AI related design and implementation in different team projects

Your Profile

Qualifications and skills to help you succeed

• A master’s degree in electrical engineering or computer science (or equivalent) and 2-3 years of related research/engineering experience
• Strong background in mathematical modeling and numerical analysis
• Knowledge of modern NN architectures, Machine Learning tools and trends
• Proficiency in Python and at least one ML framework (PyTorch or TensorFlow)
• Experience with at least one of the following: signal / speech /image / video processing / wireless communication is a plus
• Understanding of embedded systems and Knowledge of Nvidia Deep Learning framework, and familiarity with patents, papers, publications on relevant technical subject matter is a plus
• Intermediate English writing, communication, and presentation skills

Please send us your CV in English.

N-iX is looking for a Lead Machine Learning Engineer (Computer Vision) to join our external expert network.

We are looking for a Lead-level ML expert who will support our hiring process by conducting technical interviews and evaluating candidates according to our internal competency matrix. This is not a full-time project role, but a flexible collaboration where you will participate in technical interviews when needed.

Responsibilities:

• Conduct technical interviews for ML / Computer Vision candidates
• Evaluate candidates according to the competency matrix
• Assess both practical experience and theoretical knowledge
• Provide clear and structured feedback after interviews
• Validate real-world experience in building and deploying ML solutions

 Requirements:

• 6+ years of experience in Machine Learning / Computer Vision
• Experience taking ownership of technical solutions (design, decision-making, mentoring, or leading initiatives)
• Strong hands-on engineering background
• Experience working with production ML systems
• Upper-Intermediate English or higher
  Strong hands-on experience with PyTorch or TensorFlow
• Solid understanding of end-to-end ML lifecycle
  Experience with model deployment and inference optimization
• Experience with experiment tracking tools
  (MLflow, Weights & Biases, DVC, or similar)
• Understanding of distributed training concepts

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.

We are looking for a senior full-stack engineer with proven experience in AI-powered document workflows.

Requirements

• 5+ years of software development experience
• Hands-on experience building production-grade AI document pipelines — not just LLM API integration, but full pipeline design and reliability
• Comfortable working with legal/commercial document structures — contracts, agreements, leases — at a level where no explanation of the basics is needed
• Experience with PDF processing: extraction, parsing, classification at scale
• Comfortable in fast-moving, small-team environments with high autonomy

• Familiarity with AI-assisted development tools (Claude Code, Cursor, or similar)

   

• Nice to Have
  Direct experience in real estate tech or legal tech products
  E-signature or document execution workflow experience
  Background in deal or transaction management platforms

Key Responsibilities

• Build AI pipelines to ingest and process document knowledge bases (regulations, contract templates, legal frameworks) and generate structured rules and logic
• Develop document understanding features: summarization, classification, party identification, payment terms, key dates, and required actions from uploaded PDFs
• Implement document state analysis — execution status detection, document categorization, follow-up identification
• Contribute across the deal intelligence stack: contract creation, e-signing workflows, payment triggers, file management, and compliance tracking
• Work autonomously and communicate proactively — own features end-to-end

Required Tech Stack

• Next.js / React — primary framework (frontend and API)
• Supabase — database and authentication
• Vercel — deployment infrastructure
• Claude API (Anthropic) — AI layer; strong prompt engineering skills required
• TypeScript — used throughout the codebase

OneAcademy is looking for a Video Designer with strong motion design skills and hands-on experience using AI tools for commercial video production. We are building a fast-scaling education brand focused on high-performance digital content, and we need someone who can combine creativity with speed and ownership.

What You’ll Do

• Create short-form video content (Reels, YouTube Shorts, TikTok) using AI-assisted production tools
• Develop static creatives for social media and marketing campaigns
• Optimize video production workflows to improve speed, efficiency, and scalability
• Adapt content to different platforms and formats
• Work within tight deadlines while maintaining quality standards

Hard Skills & Experience

• 2+ years of strong, hands-on experience with Adobe After Effects
• Basic proficiency in Adobe Photoshop
• At least 6 months of practical experience using AI tools for commercial video production (e.g., Kling, VEO, Sora, or similar)
• Experience with prompt engineering and cost optimization of AI tools (tokens / credits management)
• Solid understanding of composition, color correction, and storytelling fundamentals

Soft Skills We Value

• High level of independence and self-management
• Strong sense of responsibility and ownership over tasks and results
• Proactive mindset
• Fast learner, comfortable adapting to new tools and workflows
• Ability to operate in a performance-driven environment

What We’re Looking For

This role is ideal for someone who is not just an executor, but a creator who understands both aesthetics and performance metrics. You should be comfortable experimenting with AI tools, iterating quickly, and continuously improving production efficiency.

If you thrive in a fast-moving, digital-first environment and want to shape the visual language of a growing education brand — we’d love to hear from you.

Why OneAcademy

• Direct ownership over growth of a core educational product
• Opportunity to build a scalable, data-driven education business
• Global product with long-term LTV focus
• High level of autonomy and fast execution
  
  What We Offer
• Ownership of acquisition strategy 
• Work with large budgets and high-scale performance campaigns
• Direct influence on unit economics and growth metrics
• Opportunity to build and shape your own team
• Remote work with flexible schedule
• Work in a fast-growing global prop trading firm
• Performance bonuses and incentives

About Us

Our client is MilTech startup building an on-premises platform for automated annotation of UAV video and training computer vision models for autonomous flight.

We have a strategic partnership with one of the largest Ukrainian UAV manufacturers and access to what is likely the largest privately owned UAV video dataset in the world.

The company is at a very early stage — the funding is secured, the technical vision exists, and the data is available. Our focus now is building the core engineering team to turn this platform into reality.

The Role

We are looking for a Lead Computer Vision / Machine Learning Engineer to join as a founding member of the engineering team.

This role is highly hands-on and strategic. You will define the ML architecture, select the tools and frameworks, and build the machine learning pipeline from the ground up. As the platform grows, you will also build and lead a team of ML engineers.

While the high-level technical direction is defined — including petabyte-scale video processing, active learning pipelines, and edge deployment on NVIDIA Jetson devices — the implementation details will be driven by your expertise and technical judgement.

Responsibilities ML Architecture & Technical Direction

• Design and implement the end-to-end ML pipeline, from raw video ingestion to model deployment on UAV hardware
• Evaluate and select appropriate frameworks and infrastructure tools
• Build systems for experiment tracking, model versioning, and reproducible training
• Establish the training infrastructure and ML development workflow
• Make strategic build vs. integrate decisions across the ML stack

Data Pipeline & Curation

• Design video preprocessing pipelines including:
   
  • clip segmentation
  • frame extraction
  • scene detection
  • embedding generation
• Develop data curation workflows to extract high-quality training datasets from large-scale raw video
• Define the annotation ontology and labeling standards for detection, classification, segmentation, and multi-object tracking

Model Development

• Train and improve computer vision models for:
   
  • object detection
  • scene classification
  • object tracking
  • segmentation
• Implement distributed multi-GPU training for large-scale experiments
• Design and implement active learning pipelines including:
   
  • automated labeling
  • confidence-based routing
  • human review workflows
  • retraining triggers
• Define model evaluation metrics and promotion criteria

Edge Deployment

• Optimize models for real-time inference on NVIDIA Jetson hardware
• Implement model optimization techniques including:
  • ONNX conversion
  • TensorRT acceleration
  • INT8 quantization
• Design the model delivery pipeline from training registry to deployed UAV systems

Team Building

• Hire and mentor ML engineers as the team grows
• Establish engineering practices including:
  • code review
  • testing standards
  • documentation
• Own and communicate the ML technical roadmap

RequirementsMust Have

• 5+ years of experience in computer vision and deep learning, including production deployments
• Strong proficiency with PyTorch, including distributed training
• Experience building object detection and tracking pipelines (YOLO, RT-DETR, Detectron2, or similar)
• Experience optimizing models for edge or mobile deployment (TensorRT, ONNX, SNPE, or similar)
• Experience building ML infrastructure and training pipelines
• Strong Python skills and ability to write production-quality code
• Experience leading or mentoring engineers

Nice to Have

• Experience with UAV, drone, robotics, or autonomous systems
• Experience deploying models on NVIDIA Jetson
• Experience with high-performance video processing pipelines (DeepStream or custom)
• Experience in defense or MilTech environments
• Experience defining ML architecture from scratch in early-stage startups
• C++ experience for performance-critical components

What We Offer

• Founding engineering role with direct influence on company technology
• Ownership of the entire ML pipeline from raw data to deployed models
• Access to one of the largest privately owned UAV video datasets in the world
• Dedicated on-prem GPU infrastructure
• Open-source-first engineering approach
• Opportunity to build and lead a machine learning team
• Competitive salary
• Stock options