Jobs ML / AI

Job Description

• Master’s or PhD in Computer Science, AI, Biomedical Engineering, or a related field.
• 7+ years of experience in AI/ML with at least 4 years focused on computer vision and deep learning.
• Proven experience with CNN architectures (e.g., ResNet, UNet, EfficientNet, VGG).
• Experience with GANs (e.g., CycleGAN, StyleGAN, Pix2Pix) and synthetic image generation.
• Hands-on with TensorFlow, PyTorch, OpenCV, and related vision libraries.
• Strong understanding of preprocessing techniques for medical imaging data (e.g., DICOM, NIfTI).
• Familiarity with training in cloud environments (Azure, AWS, GCP).
• Experience in deploying models and integrating with PACS systems or cloud-native imaging stacks.
• Solid understanding of model performance metrics and validation strategies for imaging.
• Excellent communication skills and at least Upper-Intermediate English level.

Preferred Qualifications (Nice to Have)

• Experience with FDA/CE Class B or C medical imaging products.
• Familiarity with explainable AI (Grad-CAM, LIME) and fairness techniques for imaging models.
• Knowledge of FHIR, HL7, and healthcare data standards.
• Understanding of HIPAA, GDPR, or other relevant data protection regulations.
• Experience with AI for surgical robotics, augmented reality in healthcare, or histopathology image analysis.
• Involvement in technical presales or client advisory initiatives.

Job Responsibilities

• Design, develop, and optimize AI models for computer vision, segmentation, objects detection, image classification, etc.
• Lead computer vision and AI solutioning in client engagements and presales discussions.
• Build CNN- and GAN-based architectures tailored for healthcare and medical imaging use cases.
• Prepare and preprocess large-scale datasets from modalities like X-ray, CT, MRI, and digital pathology.
• Guide annotation strategies and quality control for labeled data.
• Collaborate with cloud, DevOps, and QA teams to integrate models into production pipelines.
• Ensure model robustness, explainability, and regulatory readiness (e.g., traceability, reproducibility).
• Conduct technical workshops and communicate complex concepts to clients in an accessible way.
• Stay current with research trends and evaluate new techniques for potential integration.
• Contribute to internal accelerators, frameworks, and IP development.

Department/Project Description

Join GlobalLogic’s Architects Team within the Healthcare Business Unit, supporting clients across the EMEA region. This strategic role focuses on engaging new clients, designing advanced AI solutions for medical image analysis, and launching projects involving computer vision, deep learning, and generative AI. You’ll work on cutting-edge use cases like diagnostic assistance, surgical planning, and radiology automation, bringing meaningful impact to patient care. If you’re passionate about AI in healthcare and want to drive innovation with real-world results, we’d love to hear from you.

About the Role

We are looking for a Senior Python Backend Engineer to join a Client’s SaaS team and build production-grade backend services and large-scale LLM-powered systems.

This role requires strong backend engineering, deep service design experience, and hands-on work with LLM inference in production, including self-hosted models. You will work on scalable AI-driven services, optimize inference pipelines, and ensure reliability, performance, and cost-efficiency of LLM workloads in real-world production environments.

Location: Remote
Cooperation Type: Full-time, long-term
Experience Level: 7+ years
Start: ASAP

Responsibilities

• Design, develop, and maintain scalable backend services using Python and FastAPI
• Build and operate production-grade LLM inference pipelines
• Deploy, host, and optimize self-hosted LLM models (not only external APIs)
• Design systems for LLM request routing, batching, caching, and latency optimization
• Build high-performance APIs for AI-driven features and SaaS product workflows
• Process large-scale structured and unstructured data (text, embeddings, events, documents)
• Design and optimize PostgreSQL schemas and queries for performance and concurrency
• Build asynchronous and event-driven systems (RabbitMQ or similar)
• Monitor, debug, and optimize production systems under real traffic and load
• Collaborate with ML, Product, and Infrastructure teams on AI system architecture
• Ensure reliability, observability, scalability, and cost-efficiency of AI services
• Write clean, maintainable, and well-documented code

Requirements

• 7+ years of backend engineering experience with Python
• Strong hands-on experience with FastAPI (or Flask / Django REST)
• Hands-on experience running LLM inference in production
• Experience hosting and operating self-hosted LLM models
• Strong service design and distributed systems experience
• Experience building LLM pipelines (orchestration, routing, prompt pipelines, RAG, etc.)
• Strong experience with PostgreSQL (indexes, optimization, concurrency)
• Experience with message queues (RabbitMQ or similar)
• Experience with Docker and CI/CD
• Experience optimizing latency, throughput, and cost in high-load services
• Ability to start quickly, take ownership, and work independently
• English: Upper-Intermediate or higher

Nice to Have

• Experience with self-hosted LLM serving (vLLM, TGI, Triton, TensorRT, etc.)
• Experience with vector databases and embeddings pipelines
• Experience with GPU workloads / inference optimization
• Kubernetes or container orchestration
• Experience with RAG pipelines
• MLOps / ML infrastructure experience
• Experience with ETL / ELT pipelines

What We Offer

• Competitive compensation based on experience (gross system)
• Fully remote cooperation
• Fast hiring process and quick start
• Opportunity to work on a real AI product with immediate impact
• Direct collaboration with a client’s engineering team

What happens after you apply

• Quick CV review
• Short recruiter call
• Technical interview with LITSLINK team & technical meeting with the Client
• Fast decision & offer

We’re looking for an  AI Automation Engineer with experience in AI tools and workflow optimization to join our growing team. You’ll help us automate and scale both internal and client-side processes. This is a long-term opportunity for smart, ambitious professionals eager to grow their skills and take ownership of impactful automation systems.

What You’ll Do:

• Build and maintain n8n workflows that integrate with business tools and AI tools
• Build API integrations to platforms like Apollo, Clay, HubSpot, SalesNav, HeyReach
• Develop custom tools using Supabase, Lovable, and other AI development tools
• Optionally contribute to more technical projects and custom-coded automation or AI solutions

What You Need:

• At least 1 year of commercial experience in software development or automation
• Proficiency with n8n (or Make.com / Zapier) and understanding how to build complex automations
• Knowledge JavaScript or Python to write custom logic in workflows and 
• Being comfortable working with APIs and webhooks
• Hands-on experience with HubSpot, GHL, ActiveCampaign, or similar CRMs
• Knowledge of Cursor/Claude Code/Copilot for AI-assisted development
• Practical experience with databases(Supabase, Airtable, etc)
• Proven experience integrating AI platforms (OpenAI, Anthropic, Azure AI, etc.) into automation workflows
• Strong understanding of prompt engineering & LLM’s
• Experience working cross-functionally in distributed teams

Would be a plus:

• Deep understanding of sales pipeline

Why Join Us?

• Work on multiple dynamic projects across marketing, sales, and leadgen
• Opportunity to grow into a more technical role working with code and complex AI/automation solutions
• Shape how automation is used in real-world business contexts

Benefits:

•  Fully remote work with flexible hours 
•  Ability to influence technologies and tools used in your projects
•  20 business days of vacation per year + paid sick days
•  Accounting support provided

On behalf of our Client from the UK, Mobilunity is looking for a Senior Applied AI Engineer.

In this role, you will own and drive large portions of our AI agent infrastructure, from designing and deploying multi-agent systems to integrating Retrieval-Augmented Generation (RAG)pipelines, and evaluation frameworks. You will be responsible for delivering AI-powered features into production at scale — ensuring they are performant, reliable, and secure —while also contributing across the stack, from frontend interfaces to backend APIs, databases, and deployment pipelines.

Full-time, long-term.

Schedule:For candidates outside UK - during UK business hours.
Requirements:

• Build, test, and deploy backend services and APIs (Python/ Django/ FastAPI preferred, but other languages/frameworks welcome).
• Collaborate with founders, growth team, designers, and other engineers to deliver high-impact features.
• Ensure scalability, performance, and security across the stack.
• Develop and deploy AI-powered features in production, including RAG(Retrieval-Augmented Generation) systems, multi-agent infrastructure, and evaluation frameworks (Evals).
• Create data pipelines for AI model training, evaluation, and continuous improvement.
• Mentor junior developers and promote engineering best practices.

Requirements:

• 5+ years of professional software engineering experience.
• Hands-on experience building and deploying AI applications in production environments.
• Strong backend development skills (Python preferred)
• Solid understanding of relational databases.
• Experience with Git and collaborative development workflows.
• Knowledge of cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Strong problem-solving skills and a passion for building great products.
• Experience implementing background workers and task queues (Celery, RQ, etc.).
• Proficiency with Redis for caching, pub/sub, or job queues.
• Hands-on experience building and deploying AI applications in production environments.
• Experience implementing RAG pipelines, AI agent orchestration, and performance monitoring.
• Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety.

In return we offer

• The friendliest community of like-minded IT-people
• Open knowledge-sharing environment – exclusive access to a rich pool of colleagues willing to share their endless insights into the broadest variety of modern technologies
• Mobilunity Medical Insurance program designed to attend our teams’ needs
• Paid vacations and sick leaves, including 5 paid days per year that don’t require a sick note
• Perfect office location in the city-center (900m from Lukyanivska metro station with a green and spacious neighborhood) or remote mode engagement: you can choose a convenient one
• for you, with a possibility to fit together both
• No open-spaces setup – separate rooms for every team’s comfort and multiple lounge and gaming zones
• English classes in 1-to-1 & group modes with elements of gamification
• Neverending fun: sports events, tournaments, music band, multiple affinity groups.

Come on board, and let's grow together!

Description:
We are seeking a GenAl Developer with a strong background in Large Language Models (LLM) and GenAI engineering. This is a unique opportunity to work with Deloitte US clients and engage in global projects, leveraging your extensive skills in generative Al tools. As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative
projects

Requirements:

• Minimum of 3 years of experience as a Back End developer.
• Strong proficiency in Python and experience with microservices architectures.
• Familiarity with orchestration frameworks (langchain, langgraph, crewai, autogen etc) and API integrations.
• Knowledge of Backend Frameworks such as Node.js and Django.
• Knowledge of APIs such as JSON and REST
• Good understanding of AI protocols and standards.
• Degree in Computer Science, Artificial Intelligence, Machine Learning or a related field
• Excellent problem-solving and analytical skills.
• Experience working on global teams collaborating via tools such as Jira, Teams, ADO.

• Advanced level of English.

   

Responsibilities:

• Implement effective and scalable Python code.
• Develop and implement GenAI applications including
• Large Language Models (LLM).
• Utilize GenAl engineering tools such as LangChain, RAG, Vector Database for implementation and optimization.
• Stay updated with Al protocols and standards and ensure their correct application in projects.
• Collaborate with other team members to understand requirements and develop solutions.
• Analyze complex problems, identify and define the computational requirements to solve them.

We are hiring a Senior AI Engineer to build the core AI system behind a high-impact project: digitizing law in Morocco and Africa and creating the first AI-queryable legal knowledge base.

Our goal is to deliver reliable, source-grounded answers to legal questions, based on a large corpus of heterogeneous legal documents.

🚀 Why this project

• Build a legal knowledge infrastructure, not a demo
• Work on high-precision AI where accuracy, traceability, and reliability matter
• Create a long-term asset (Morocco → Africa) with real societal impact

🎯 Your mission

Own the end-to-end AI pipeline:

Legal documents → structured data → retrieval → cited answers

You will design, build, and improve both the document processing pipelines and the RAG/search system, with a strong focus on quality, evaluation, and robustness.

🔧 Key responsibilities

• Process and structure heterogeneous legal documents (PDFs, scans, Word, images):
  • parsing, OCR, cleaning, structuring (articles, sections, hierarchy)
  • intelligent chunking with full traceability and metadata
• Build and improve retrieval & RAG:
  • hybrid search (BM25 + embeddings)
  • reranking (cross-encoders)
  • query understanding and expansion
• Ensure grounded, reliable answers:
  • strict citation to sources
  • no-answer / controlled refusal when evidence is missing
• Measure and improve quality:
  • evaluation datasets, relevance metrics (Recall@k, MRR, nDCG)
  • regression testing and error analysis
• Production readiness:
  • robust pipelines, monitoring, logging, performance

✅ Profile

• 5+ years of experience in AI / NLP / Search / Data Engineering roles
• Strong Python skills
• Hands-on experience with unstructured documents and/or RAG systems
• Strong culture of measurement and experimentation
• Professional proficiency in English, French is a plus.

🛠 Tech stack (indicative)

• Document processing & OCR tools
• Retrieval: OpenSearch / Elasticsearch, vector search (FAISS, pgvector, etc.)
• Reranking: HuggingFace / cross-encoders
• RAG orchestration: LangChain or LlamaIndex (nice-to-have)
• Cloud: AWS

Experience
7+ years of backend engineering experience

About the Role
We’re a rapidly growing startup building data- and AI-driven systems at scale. We’re looking for a Senior Backend Engineer who thrives on ownership — someone who designs systems, ships them to production, and takes responsibility for their reliability, performance, and long-term quality.
You’ll own core backend services and data pipelines that handle high-volume structured and unstructured data, power AI workflows, and serve LLMs in production. This is a hands-on role with real impact and minimal process overhead.

What You’ll Do
• Own and build core backend services with modularity using Python and FastAPI
• Design and maintain production-grade APIs for data ingestion, processing, and model inference • Build systems that handle high-volume structured and unstructured data (text, documents, embeddings, events)
 • Design and operate AI data pipelines that support ingestion, transformation, and serving
 • Support hosting, scaling, and serving LLMs and other ML models in production
 • Design and optimize PostgreSQL schemas and queries for performance and reliability
 • Build asynchronous and event-driven systems using RabbitMQ
 • Make pragmatic architecture decisions with a focus on simplicity, correctness, and scalability
 • Ensure systems are observable, fault-tolerant, and easy to operate
 • Take responsibility for production issues, debugging, and continuous improvement
 • Set a high bar for code quality, testing, and maintainability
 • Collaborate closely with product, frontend, and ML teams

What We’re Looking For
Core Backend & Systems
• 7+ years of backend engineering experience
• Strong proficiency in Python, including async programming
• Extensive experience with FastAPI or similar modern frameworks
• Strong fundamentals in API design, authentication, and security
• Deep experience with PostgreSQL (schema design, indexing, query optimization, migrations, concurrency)
• Hands-on experience with RabbitMQ or similar systems (queue design, retries, backpressure, failure handling)

Preferred Data & AI Experience
• Experience handling large-scale structured and unstructured data
• Experience building or supporting AI/ML data pipelines
• Exposure to LLM inference systems (self-hosted or managed)
• Ability to design backend systems that evolve as models and data change

Deployment & Reliability
• Strong experience with Docker and containerized deployments • Familiarity with CI/CD and automated releases
• Strong focus on reliability, observability, and operational quality

Nice to Have
• Kubernetes or container orchestration experience
• Experience running compute-intensive or GPU-backed services • Experience with vector databases or search systems

Job Description

We’re looking for a skilled Lead Python Engineer to join our team in building and scaling LLM-powered applications. You’ll be working with modern agentic AI frameworks, designing APIs, and integrating with cloud services – primarily on Azure.

• 6+ years of experience as a Python AI Engineer.
• Strong experience with FastAPI, SQLAlchemy, and PyTest.
• Experience with agentic AI frameworks (e.g., Haystack, LangGraph, CrewAI).
• Familiarity with LLM-based systems and integration patterns.
• Working experience of Docker, Kubernetes, and Git.
• Hands-on experience with Azure cloud services (especially Azure AI, Azure Functions, etc.).
• Familiarity with PostgreSQL.
• Experience with Retrieval-Augmented Generation (RAG), including vector databases and embeddings.
• Experience with Langfuse or similar LLM evaluation/monitoring tools.
• Experience with CI/CD workflows and observability tools.
• Interest in emerging LLM/agentic tooling and frameworks.
• Solid understanding of natural language processing techniques, with experience in deploying NLP systems and working with prompt libraries.
• Expertise in data analysis and analytics.
• Proven track record of driving innovation and solving complex technical problems using AI and machine learning.
• Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Experience working collaboratively within cross-functional teams.
• Understanding of data privacy and security standards, ensuring systems are compliant with industry regulations and best practices.
• Passion for continuous learning and staying updated with the latest trends and advancements in AI/ML technologies.
• Experience with multi-agent architectures.
• Experience with MCP protocol.
• Demonstrated experience in leading technical teams and managing complex projects from start to finish.

Job Responsibilities

• Collaborate with PO, BA, stakeholders to understand the specific needs and requirements of the business process.
• Translate business needs into technical specifications.
• Collaborate with frontend engineers, Data Scientists, and DevOps to deliver scalable LLM solutions.
• Lead technical team to ensure the deadlines and quality standards are met.
• Develop and maintain backend services using FastAPI.
• Work with agentic AI frameworks like Haystack to build AI pipelines and components.
• Design and implement robust database models using SQLAlchemy with PostgreSQL.
• Write and maintain unit and integration tests using PyTest.
• Deploy services using Docker and Kubernetes.
• Utilize Azure services (e.g., Azure AI) for hosting, inference, and other cloud-native features.
• Use Langfuse or similar tools for LLM performance monitoring and evaluation and implement improvements as necessary.
• Develop and refine the prompt library to facilitate seamless user interaction and request handling.
• Ensure the AI models integrate effectively with existing applications and workflows.
• Conduct thorough testing of AI models to ensure they meet quality, performance, and accuracy standards.
• Provide ongoing support and troubleshooting to address any system issues.
• Monitor and adapt AI systems to accommodate changes in the business process or user requirements.

• Create comprehensive documentation for developed solutions.

   

Department/Project Description

Global player in the railway sector is looking to create an internal platform aimed to support the Bid and Sales teams during critical stages of the bidding process, as well as to assist to Engineers throughout key phases of the Engineering projects lifecycle.

This solution utilizes various techniques, including multi-agent GenAI, to enhance the requirements and compliance process, facilitate data analysis and tender authoring, provide guidance in engineering, offer technical support, and aid in decision-making. It also generates essential artifacts such as requirements, designs, and tests. Additionally, the solution will enable data analytics to identify trends across bids, supporting the Sales and Product Development teams.

We are looking for a Senior Machine Learning Engineer to take ownership of the AI core of our orthodontic platform.

We already have a working production system and existing ML models operating on 3D dental data (STL files). The challenge is not to build everything from scratch, but to understand, improve, retrain, and evolve an existing ML stack as the product enters a new MVP phase.
 

The original development team is no longer available, and we are now simplifying and refocusing the product. This role is about turning an existing, complex ML system into a clean, reliable, and extensible AI foundation that can support a scalable orthodontic product.

You will work directly with the founder and a small senior engineering team. Decisions are fast, communication is direct, and your technical judgement will directly shape both the product and the AI roadmap.

This is not a Kaggle-style research role.

This is real production ML on 3D medical data, with business and clinical impact.
 

What you will work on

• Taking ownership of existing ML models used for orthodontic / dental analysis
• Understanding, retraining, fine-tuning, and improving current models
• Modifying or extending model architectures when needed
• Potentially designing and training new models when existing ones no longer fit the product
• Working with STL files and 3D dental geometry as model inputs
• Collaborating closely with backend engineers to integrate models into production pipelines
• Ensuring models are stable, reproducible, and production-ready
   

What we are looking for

• Strong experience as an ML Engineer in production systems
• Ability to read, understand, and modify existing ML codebases
• Experience training, fine-tuning, and validating models (not just using pretrained ones)
• Solid Python + ML stack (PyTorch / TensorFlow or similar)
• Comfort working with geometric, spatial, or 3D data
• Ability to reason about trade-offs between model accuracy, performance, and engineering constraints
   

Domain-specific requirements

• Experience working with STL files or 3D mesh data
• Understanding of 3D geometry, point clouds, meshes, or surface models
• Familiarity with dental / orthodontic software (e.g. 3Shape, or similar) is a strong plus
   

Nice to have

• Experience with medical, dental, CAD, or 3D scanning data
• Experience deploying ML models into backend systems (APIs, pipelines, batch jobs)
• AWS or cloud experience
• Interest in building end-to-end AI products, not just isolated models
   

This role is for someone who enjoys working at the intersection of ML, 3D geometry, and real-world medical applications — and who wants to have a real influence on how an AI-driven product is rebuilt and scaled at a critical stage.

TRENDFORMER is an innovative product company because we don’t just make toys. We create new products and experiences for entertainment and self-expression, devices that release and develop the natural creative potential in every human being.

At TRENDFORMER we’re changing the face of play.

The professional and creative team of the Company has created and brought to the international market its own unique products under the brands PIXIO (https://pixio.site/), HEY CLAY (https://hey-clay.com/) and VOXART (https://vox.art/). Our products are successfully sold in more than 30 countries. They aimed to spark creative potential and take on a fantastic journey of discovery and crafts, entertain and develop children through play.

We’re looking for experienced and talented AI Video Makers / AI Animators with a proven background in creating animated video content using modern neural networks and AI tools.

Your responsibilities:

• Create animated AI-driven video content, including short-form videos, scenes, and concept reels;
• Develop storyboards and animatics, defining visual logic, narrative structure, pacing, and rhythm;
• Define visual style and references, test different creative approaches, tools, and pipelines;
• Assemble and edit videos using AI-generated frames, animation, effects, transitions, and sound, ensuring strong storytelling and rhythm;
• Maintain high visual quality and consistency across all deliverables, including style cohesion, scene logic, and pacing;
• Collaborate closely with the team: receive feedback, iterate quickly, and deliver polished final results within deadlines.

Our ideal candidate has:

• 1+ years of experience in video creation, animation, or AI-driven video production;
• A strong showreel (required), with a clear focus on AI-generated and animated video content;
• Hands-on, consistent experience using AI and neural networks in a production pipeline;
• Strong artistic vision, including a sense of composition, rhythm, style, and visual cohesion;
• Excellent attention to detail, taste, and creative judgement;
• Ability to work independently, take responsibility for tasks, and manage time effectively under tight deadlines;
• Strong teamwork skills and a professional approach to feedback and revisions;
• Willingness to complete a test task.

Additional skills & tools (nice to have):

• Experience in motion design, VFX, compositing, or art direction;
• Character animation or stylisation experience;
• Skills in clean-up, upscaling, denoising, stabilisation, and flicker control;
• Basic sound design skills, including music selection and syncing with rhythm;
• Understanding of short-form content formats (TikTok, Reels, Shorts) and fast-paced editing language;
• Experience working with collaborative pipelines and tools (Notion, Figma, Google Drive, Frame.io, or similar);
• Hands-on experience with AI video generation tools, editing software (Premiere Pro, After Effects, DaVinci Resolve, CapCut, etc.), and post-production enhancement tools.

We offer:

• The opportunity to shape globally recognized products that kids and families love;
• Flexible work format (remote or hybrid);
• A supportive, creative, and forward-thinking team;
• Open-door culture and direct communication;
• Competitive salary (negotiable based on engagement format and experience).

How to Apply:

Please send:

• А short intro about yourself (2–5 sentences)
• Your showreel / portfolio
• A LinkedIn link or CV (optional)
• Confirmation that you are ready to complete a test task

If you love combining technology + strong artistic vision, can quickly assemble animated scenes, enjoy exploring new tools, and know how to work with feedback — we’d love to meet you!

About The Position

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps and FinOps and GenAI support that drives real results.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We seek an experienced Senior AI Engineer to join our team. You will work hands-on with innovative startups' Data Science and R&D teams and be in charge of various projects. You will develop robust MLOps pipelines, create cutting-edge Generative AI solutions, implement the latest technologies, and ensure the customers’ success by overseeing the project from inception to completion.

📍 Work location - remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• Developing backend Generative AI solutions and POCs, utilizing RAG pipelines, agent-based systems, and LLM-powered services
• Taking existing ML or customer-provided code and adapting it for training, fine-tuning, and production deployment using PyTorch
• Developing and optimizing fine-tuning workflows, model evaluation, benchmarking, and inference optimization
• Provision of ML AWS resources and infrastructure primarily using managed and cloud-native services
• Developing ML-oriented CI/CD pipelines using GitHub Actions, Bitbucket, or similar tools
• Deploying Machine Learning models in production and ensuring they are observable and monitorable
• Collaborating with Solution Architects and DevOps teams on scalable and cost-efficient AI infrastructure
• Learning new skills and technologies quickly to stay up to date with rapidly evolving GenAI tools
• Using and writing Terraform libraries for infrastructure deployment
• Maintaining infrastructures and environments of all types, from dev to production
• Security monitoring and administration

Requirements

• Excellent customer-facing skills to understand and address client needs effectively
• Ability to design and implement cloud solutions and to build GenAI pipelines on AWS
• Experience with one or more large language model frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex
• Fluency in Python, a good understanding of Linux, and mandatory hands-on production experience with PyTorch
• Ability to understand tools used by data scientists and experience with building Generative AI applications beyond notebooks or demos
• Good understanding of supervised and unsupervised learning, and deep learning concepts
• Fluent written and verbal communication skills in English
• Ability to work hands-on, independently, and deliver under real project constraints
• Bachelor’s or Master’s degree in AI-related fields - an advantage
• Working knowledge of some Vector Databases (OpenSearch, Qdrant, Weaviate, LanceDB, etc.) - an advantage
• Experience with Docker and Kubernetes - an advantage
• Experience with Azure or GCP (DevOps/MLOps) for ML or GenAI workloads - an advantage
• ML certification (AWS ML Specialty or similar) - an advantage

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our team.

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.

Description

Our Client is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. 

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.

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.

Requirements

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 –esp when moving from dev into prod

We are looking for a hands-on AI Engineer to build and integrate AI-powered features while handling regular backend development tasks. You’ll work across the stack to bring intelligent features into products - from prototyping with AI models to implementing APIs and business logic.

Responsibilities:
• Develop and integrate AI-powered features (e.g., chatbots, recommendation engines, image/video analysis);
• Use pre-trained models and APIs (OpenAI, Hugging Face, etc.) or fine-tune existing models;
• Implement backend services and APIs;
• Optimize AI functionality for performance, scalability, and cost-efficiency;
• Monitor and improve AI performance in production;
• Stay up to date with recent advances in AI/ML tools and frameworks.

Requirements:
• 4+ years of experience as a software developer;
• At least 1 year of experience in AI development (including commercial work, pet projects, or non-commercial experience);
• Strong experience with AI/ML frameworks and model APIs (e.g., Hugging Face, OpenAI);
• Hands-on experience building LLM-based solutions using LangChain, RAG, and similar tooling;
•Understanding of LLMs, embeddings, vector databases, and prompt engineering;
• Language-agnostic mindset with readiness to work in different backend languages, such as Python, Node.js, or PHP;
• Ability to design and implement RESTful APIs;
• Ability to write clean, maintainable, and scalable code;
• Strong problem-solving skills and ability to translate business needs into technical solutions;
• Bachelor’s degree in Computer Science or related field.

Nice to Have:
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch);
•Experience with cloud platforms (AWS, GCP, Azure).

We offer:
• Transparent financial motivation;
• Remote workplace or a comfortable office in the center of Kyiv;
• 18 working days of paid leave annually;
• Unlimited sick days;
• Salary review twice a year;
• Compensation for our English-speaking club — 100%;
• Compensation for any AI tool of your choice — 100%;
• Compensation for coworking spaces — 100%;
• Compensation for gym memberships and professional courses — 50% (after the trial period);
• Compensation for any English courses — 50% (after the trial period);
• Compensation for sessions with a psychologist — 50% (after the trial period);
• Medical insurance (after the trial period).

Interview Stages:
Screening Interview ➡️ Technical Interview ➡️ Job Offer

If you have the skills, passion, and determination we’re looking for, apply now to become part of our exciting journey⭐

We're hiring Low-Level Engineers to design and build RL environments that teach LLMs kernel development, hardware optimization, and systems programming. The goal is to create realistic feedback loops where models learn to write high-performance code across GPU and CPU architectures.

This is a remote contractor role with ≥4 hours overlap to PST and advanced English (C1/C2) required.

Requirements

Minimal Qualifications

• Strong Python (engineering-quality, not notebook-only)
• Production mindset (debugging, reliability, iteration speed)
• Clear understanding of LLMs, their current limitations
• Ability to meet throughput expectations and respond quickly to feedback

You may be a good fit if one of the following applies

• Deep understanding of memory hierarchies (registers, L1/L2/shared memory, HBM, system RAM) and their performance implications
• Threading models, synchronization primitives, and concurrent programming (warps, thread blocks, barriers, atomics)
• Cache coherence, memory access patterns, coalescing, and bank conflicts
• JIT compilation frameworks (e.g., Triton, JAX/XLA, TorchInductor, Numba)
• AOT compilation and optimization passes (LLVM, MLIR, TVM)
• Compiler and kernel frameworks such as CUTLASS, BitBLAS, or JAX/Pallas
• Modern C++, including templates, concurrency, and build systems
• Assembly-level programming and low-level optimization across GPU and CPU architectures (e.g., x86, ARM, NVIDIA Hopper, NVIDIA Blackwell)
• Debugging and optimizing GPU kernels using CUDA and/or HIP/ROCm
• Developing PyTorch custom operators, backend extensions, or dispatcher integrations (e.g., ATen, TorchScript, or custom backends)
• Customizing, extending, or optimizing c, including distributed inference workflows
• GPU communication libraries and collectives, such as NVIDIA NCCL, AMD RCCL, MPI, or UCX
• Mixed-precision and low-precision kernels (e.g., FP16, BF16, FP8, INT8), including numerical stability and performance trade-offs