Jobs ML / AI Engineer

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.

AI Engineer Intern (AI Agents)

🚀 About Fuller Focus

Fuller Focus is building the data layer for companies selling to nonprofits.

Right now, most teams waste time targeting organisations that will never buy. We fix that by helping them identify who to contact and when.

We’re early, moving fast, and working directly with customers to build what matters.

🧠 The Role

We’re looking for an AI Engineer Intern to build AI agents that replace manual research work.

This is not a “learn and watch” internship. You’ll be shipping real systems used in production.

⚡ What You’ll Work On

Examples of what you might build:

• AI agents that email organisations and parse responses
• Voice agents that call organisations to collect missing data
• Automated workflows that replace human research tasks
• Systems that collect proprietary data at scale
•  

🎯 What Success Looks Like

By ~week 8:

You’ve built an AI agent that replaces a human researcher and collects production-level data at scale.

🧰 What We’re Looking For

You must be a builder.

• You’ve built things (AI projects, agents, tools — not just coursework)
• You have a strong GitHub or portfolio
• You’re comfortable working with APIs (e.g. LLMs like Anthropic/OpenAI)
• You can figure things out without step-by-step instructions
• You enjoy experimenting and shipping quickly

✅ Strong Signals

• You’ve built AI agents before
• You’ve shipped side projects end-to-end
• You’ve worked with messy, real-world data
• You have a startup / hacker mindset

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.

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are seeking an experienced Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and prototype data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines, design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and do end-to-end LLMs training. You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards.

Responsibilities:
- Curation of datasets for pre-training, supervised fine-tuning, and alignment
- Research and develop best practices and novel techniques in LLM training and evaluation pipelines.
- Collaborate closely with data engineers, annotators, linguists, and domain experts to scale data processes, define evaluation tasks and collect high-quality feedback.

Requirements:
Education & Experience:
- 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
- An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
GenAI & NLP Expertise:
- Practical experience with fine-tuning LLMs / VLMs models
- Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
ML & Programming Skills:
- Strong experience with deep learning frameworks such as PyTorch or JAX for building models.
- Ability to write efficient, clean code and debug complex model issues.

Nice-to-have:
Advanced NLP/ML Techniques:
- Applied experience using Reinforcement Learning in NLP / LLM settings
- Prior work on LLM safety, fairness, and bias mitigation.
- Experience generating and curating synthetic datasets for Supervised Fine-Tuning (SFT), including quality control and scaling considerations.
Research & Community:
- Publications in NLP/ML conferences or contributions to open-source NLP projects.
- Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.
MLOps & Infrastructure:
- Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
- Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.
- Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.
Problem-Solving:
- Innovative mindset with the ability to approach open-ended AI problems creatively.
- Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation

The company offers:
- Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
- Remote onboarding
- We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
- Health and life insurance
- Wellbeing program and corporate psychologist
- Reimbursement of expenses for Kyivstar mobile communication

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role:
We are looking for a hands-on Sr. Machine Learning / Computer Vision Engineer with strong practical experience in designing, training, evaluating, and improving vision systems for real-world applications. The ideal candidate combines solid theoretical ML/CV fundamentals with an engineering mindset and is comfortable taking ownership of the full pipeline, from data preparation and experimentation to model optimization and deployment.

Responsibilities:
- Design, train, evaluate, and improve machine learning and computer vision models for real-world production use cases
- Build and maintain end-to-end ML pipelines, including data collection support, preprocessing, feature engineering, training, validation, and inference
- Develop solutions across both computer vision and machine learning tasks depending on business needs
- Perform error analysis, diagnose model weaknesses, and drive improvements in accuracy, robustness, and reliability
- Select and justify appropriate methods and model architectures based on dataset characteristics, product constraints, and deployment requirements
- Work with challenging real-world data, including noisy, limited, imbalanced, or weakly labeled datasets
- Collaborate with engineering and product teams to translate business problems into practical ML solutions
- Contribute to production-ready development with a focus on maintainability, reproducibility, and performance

Requirements:
- 3–5+ years of professional experience in Machine Learning / Computer Vision
- Strong senior-level practical expertise in computer vision, machine learning, and applied model development
- Hands-on experience with tasks such as object detection, image classification, anomaly detection, feature-based approaches, or similar
- Solid understanding of classical ML methods, including tree-based models, linear models, feature engineering, model selection, and evaluation
- Strong Python skills and practical experience with PyTorch, OpenCV, and common ML tooling
- Experience building full ML workflows including data preparation, augmentation, preprocessing, training, validation, testing, and deployment handoff
- Strong understanding of model evaluation, debugging, overfitting, generalization, optimization, and experiment-driven improvement
- Ability to write clean, modular, maintainable code and independently own technical solutions
- Strong analytical thinking, engineering maturity, and problem-solving skills

Nice to Have:
- Experience in adjacent ML domains such as time-series, audio, or NLP
- Experience with embedding-based methods, metric learning, retrieval systems, or memory-bank approaches
- Practical experience with model optimization techniques such as quantization, pruning, distillation, or related efficiency-focused approaches
- Experience working with real-world industrial datasets and ambiguous problem formulations
- Knowledge of software engineering best practices, reproducible experimentation, and pipeline design

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

We are looking for a Senior Data Scientist with strong technical expertise and a practical mindset to work on complex data-driven challenges. In this role, you will design and implement ML and GenAI solutions, experiment with modern approaches, and transform ambiguous business problems into scalable, production-ready systems.

Requirements
Must-have

• 4+ years of experience in Data Science
• 4+ years of hands-on experience with Python
• Strong understanding of Machine Learning fundamentals, including:
  • regression and classification models
  • feature engineering and model evaluation
• Practical experience with LLMs and GenAI, including:
  • GPT / ChatGPT or similar LLMs
  • LangChain
  • Retrieval-Augmented Generation (RAG)
• Experience with EDA, data preprocessing, and basic dimensionality reduction (e.g. PCA)
• Hands-on experience with tree-based models (e.g. XGBoost)
• Experience building scalable and high-load solutions
• Ability to write clean, maintainable code
• Participation in technical and architectural decisions
  
  Nice to have
• Experience with NLP libraries (SpaCy, Hugging Face)
• Understanding of Explainable AI (XAI) and model interpretability
• Experience with cloud platforms (AWS / GCP / Azure)
• Ability to translate business problems into ML solutions

• Background in R&D, experimentation, or prototyping

  
  Key Responsibilities

• 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;
• Conduct R&D activities: explore new ML/GenAI techniques and assess their practical impact.
• Collaborate with engineering, product, and business teams to deliver impactful data-driven solutions.
  
  We offer:
• Great networking opportunities with international clients, challenging tasks;
• Building interesting projects from scratch using new technologies;
• Personal and professional development opportunities;
• Competitive salary nominated in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

   

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

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of a fast-growing software product company in advanced manufacturing.
• Learn and fulfil your potential in an open, knowledge-driven culture.
• Share in our ambitious vision and make a meaningful difference towards autonomous manufacturing.

Responsibilities: 

• Develop, test, and deploy generative AI based solutions.
• Design and implement end-to-end AI solutions that integrate with existing systems. 
• Collaborate with software engineers and product teams to understand business needs and translate them into technical solutions. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. 
• Proven experience in developing generative AI or machine learning models.
• Commercial experience in using large language models.
• Programming skills in languages such as Python or JavaScript.
• Familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization (Docker, Kubernetes) is beneficial. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

Format: Full-time

Level: Senior

Location: Remote

Salary: from $4000/month

About Workeron AI

Workeron AI is an AI Product Builder and AI Transformation partner. We create AI agents, multi-agent systems, internal AI tools, and AI-powered digital employees for founders, teams, and businesses.

We build fast, execution-focused AI products at the intersection of business, automation, and applied intelligence. Our goal is not just to develop software, but to launch working AI solutions that generate measurable value in real workflows.

We are looking for a strong senior-level builder who can independently design, prototype, and launch AI products, agentic systems, and scalable technical foundations for future growth.

Role mission

Your mission is to lead the technical creation of AI agents, multi-agent systems, and rapid product prototypes - from architecture and first implementation to deployable MVPs and pilot-ready solutions.

This is not a narrow executor role. We are looking for a senior engineer with strong product sense, system thinking, and startup execution speed - someone who can take raw ideas, shape technical solutions, build quickly, and help turn prototypes into real products.

What you will do

• Lead development of AI agents, multi-agent systems, and AI-powered product features
  
   
• Design and build production-minded MVPs and prototypes with high speed
  
   
• Define and implement client-server architecture for agentic products and workflows
  
   
• Build backend systems for orchestration, memory, tool execution, logging, permissions, and integrations
  
   
• Integrate LLMs, APIs, data sources, vector search, automations, and external services
  
   
• Create lightweight but strong user-facing products, internal tools, dashboards, and landing pages
  
   
• Make architecture decisions that balance speed, flexibility, and future scalability
  
   
• Work directly with founder and product direction to validate product hypotheses fast
  
   
• Bring technical clarity into ambiguous product ideas
  
   
• Improve system reliability, observability, evaluation quality, and iteration speed
  
   
• Support deployment, testing, iteration, and evolution from demo to stable product
  
   
• Contribute to technical standards, stack decisions, and engineering best practices inside the product builder
  
   

What we expect

Core requirements

• 5+ years of commercial development experience
  
   
• Strong hands-on experience in Python and/or JavaScript/TypeScript
  
   
• Solid experience building AI products, LLM applications, or agentic systems
  
   
• Proven track record of shipping fast MVPs, prototypes, and real user-facing products
  
   
• Strong experience with client-server architecture, APIs, and backend systems
  
   
• Ability to independently move from idea to architecture to working implementation
  
   
• Strong product thinking and business understanding
  
   
• High ownership and ability to work with minimal supervision
  
   
• Comfortable operating in ambiguity and fast-changing startup environments
  
   

AI / ML / agentic systems

• Strong practical experience with LLM APIs and model integration
  
   
• Experience with RAG, embeddings, vector databases, tool calling, structured outputs
  
   
• Experience building agents, multi-step reasoning systems, or multi-agent workflows
  
   
• Understanding of prompt engineering, memory design, context handling, evaluation, guardrails, and hallucination mitigation
  
   
• Understanding of latency, token economics, cost optimization, and AI system tradeoffs
  
   
• Experience with relevant frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar
  
   
• Practical understanding of how to make AI systems useful, reliable, and commercially testable
  
   

Backend / system design

• Strong experience building APIs and backend services
  
   
• Experience with frameworks such as FastAPI, Node.js, NestJS, Express, or similar
  
   
• Strong knowledge of PostgreSQL, Redis, and general database/system design
  
   
• Experience with queues, async tasks, background jobs, webhooks, and event-driven flows
  
   
• Ability to design modular, pragmatic, and extensible architecture
  
   
• Strong understanding of auth, access control, logging, monitoring, and failure recovery
  
   
• Ability to build systems that are fast to launch but clean enough to evolve
  
   

Frontend / product packaging

• Ability to build simple, clean, and functional UI for MVPs, internal tools, and demos
  
   
• Experience with React, Next.js, or similar frontend stack
  
   
• Ability to launch product landing pages and validation pages quickly
  
   
• Understanding of user flows, UX basics, and product packaging for early-stage launches
  
   

DevOps / deployment

• Experience with Docker
  
   
• Experience deploying apps to AWS, GCP, Vercel, Railway, Render, or similar platforms
  
   
• Good understanding of CI/CD basics
  
   
• Ability to independently deploy, debug, and maintain working environments
  
   

Nice to have

• Experience with voice agents, assistants, transcription, or multimodal systems
  
   
• Experience with automation tools such as n8n, Make, or Zapier
  
   
• Experience with Supabase, Firebase, or similar fast-build stacks
  
   
• Experience in startup, product studio, or AI-native environments
  
   
• Experience building landing pages, waitlists, and fast test funnels for validating products
  
   
• Experience mentoring other developers or acting as technical lead on small teams
  
   
• Experience with analytics, A/B tests, telemetry, and product experiment infrastructure
  
   

Who fits this role well

• You are a senior builder, not just a task executor
  
   
• You can make strong technical decisions under uncertainty
  
   
• You understand how to turn business hypotheses into technical products
  
   
• You know how to prototype quickly without creating chaos
  
   
• You are pragmatic and product-oriented
  
   
• You care about shipping, validation, and measurable outcomes
  
   
• You are excited by AI, automation, and the future of digital workers
  
   
• You want to help build a serious AI product direction from an early stage
  
   

What is especially important for us

• Seniority in judgment, not only years of experience
  
   
• Speed with technical depth
  
   
• Ability to work across backend, AI, architecture, and lightweight product interfaces
  
   
• Readiness to own a problem end-to-end
  
   
• Strong execution discipline
  
   
• Curiosity, autonomy, and startup resilience
  
   
• No overengineering for the sake of overengineering
  
   

Interview focus

During the interview we will assess:

• depth of real AI/LLM experience
  
   
• ability to architect agentic systems
  
   
• speed of prototyping and execution quality
  
   
• maturity in backend and system design
  
   
• ability to build end-to-end product prototypes
  
   
• ability to choose pragmatic technical solutions
  
   
• product sense, ownership, and communication
  
   

Example tasks in the role

• Build and launch an AI agent that connects to user tools, understands context, and executes actions
• Design a multi-agent workflow for a business use case and deploy it as a pilot
• Build a backend for orchestration, memory, and external integrations
• Create a working landing page + MVP flow for a new AI product hypothesis
• Turn a founder idea into a testable product in days or weeks
• Improve an early prototype into a stable architecture for scaling
  
   

We offer

• Salary from $4000/month
• Work on real AI agents, digital workers, and applied AI products
• Direct collaboration with founder on product direction
• High ownership and strong influence on architecture and technical decisions
• Fast-moving environment with low bureaucracy
• Opportunity to grow into Lead AI Engineer, Head of Product Engineering, or future technical leadership role
• Remote-first format
• Real impact on what gets built and how fast it reaches the market
  
   

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.
WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand
Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Essential

• GCP (esp Vertex, BigQuery, Model Registry)
• Python (needs to be very strong)
• Docker
• FastAPI (or similar)
• SQL
• Terraform
• Strong understanding or even hands-on ML experience
• Package management (uv is cool, but don’t mind others e.g. poetry; we work with a whole range here)
• Scalable experimentation & model tracking (no specific tech as we’re using native GCP logging and metadata store atm, but as we mature open-source tech e.g. MLFlow will be brilliant), and Scalable ML deployment experience (i.e. standing up an inference endpoint for hardly no traffic doesn’t count)

Desirable:

• FTI (Feature/Training/Inference) framework
• Common ML frameworks (such as PyTorch, Sklearn)

Bonus:

• RAG
• LLM orchestration tool e.g LangGraph,
• Reinforcement Learning tools e.g. OpenaiGym, RLib

Job Responsibilities

The Machine Learning Engineer is responsible for deploying and maintaining the algorithms developed by data scientists. This role will be part of the Optimize Data Science team (3 FTEs plus seconded team of 5 FTEs)

While Data Scientists focus on research and model development, the ML Engineer is responsible for the technical infrastructure, scaling, performance optimization, and maintenance of the models. Their work involves implementing, testing, deploying, and monitoring the models in a production environment.

• Model deployment: Takes models (brand new or improvements to existing models) developed by data scientists and builds the software and infrastructure to deploy them into a live production environment.
• Performance optimization: Optimizes code for latency and efficiency across different hardware, like CPUs and GPUs, and overall quality (e.g. readability, maintainability, reliability and so forth).
• System design & scaling: Designs, builds, and maintains the technical components that integrate into existing software to train, deploy, and scale ML models. (N.B. There will be opportunity to work on new systems from ground up later in the year, too.)
• Monitoring and maintenance: Implements logging and monitoring to track model performance, identifies and fixes bugs (in collaboration with wider teams if appropriate), and performs necessary updates and improvements.
• Collaboration: Works closely with data scientists and wider engineering teams to understand the model and help convert it into a production-ready system.
• Experimentation: Design, build and deploy technical components based on the methodologies designed by Data Scientists to enable scalable experiments, model evaluation and visualisation of results.
• Up-skilling DS in ML Engineering and AI innovations: Support DS team to utilise modern and cloud-based (esp GCP) technologies for development (e.g. Vertex, Docker, BigQuery, Dev Containers, Ray and others) to expedite and innovate the entire development lifecycle

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.