Вакансии Data Scientist / Machine learning Engineer

The AI and Data Science Center of Excellence (CoE) is SoftServe’s premier AI/ML hub, primarily based in Europe. With 130+ experts – including data scientists, research analysts, MLOps engineers, ML and LLM architects, we cover the full AI lifecycle, from problem framing to deployment.
In 2024, we delivered 150+ AI projects, including over 100 focused on Generative AI, combining scale with measurable impact. We are a 2024 NVIDIA Service Delivery Partner and maintain strong collaborations with Google Cloud, Amazon, and Microsoft, ensuring our teams always work with cutting-edge tools and technologies. We also lead Gen AI Lab – our internal innovation engine focused on applied research and cross-functional collaboration in Generative AI. In 2025, a key area of innovation is Agentic AI where we design and deploy autonomous, collaborative agent systems capable of addressing complex, real-world challenges at scale for our clients and internally.

If you are

• Educated with a master's or bachelor's degree in computer science or a related field
• Experienced in generative AI and NLP techniques, including large-scale transformer models and generative pre-trained LLMs such as GPT-4, Claude, and Gemini
• Knowledgeable in diffusion models and other generative frameworks for both text and image generation
• Competent in applying generative AI and language models to lead innovative NLP and AI-driven initiatives
• Proficient with state-of-the-art pre-trained language models like GPT-4, BERT, and their advanced versions, including fine-tuning for specialized use cases
• Aware of the software development lifecycle and operationalization of machine learning in AI projects
• Experienced in deploying AI solutions across major cloud providers
• Hands-on with Python and AI development frameworks
• Analytical with strong interpersonal and problem-solving skills
• Clear in translating complex technical concepts for non-technical audiences
• Capable of maintaining business-level communication in English at an upper-intermediate level

And you want to

• Develop and implement advanced Generative AI applications, including intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative solutions
• Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using cutting-edge techniques
• Work with the full stack of data analysis, deep learning, and machine learning pipelines, including customer data analysis, modeling, and production deployment
• Select appropriate computational tools for research objectives and experiments
• Present results to stakeholders and gather business requirements
• Build expertise in state-of-the-art Generative AI techniques and methodologies
• Grow your skills within a dynamic and supportive environment
• Build and operationalize ML models, including data manipulation, experiment design, analysis planning, and insight generation

We’re looking for a Senior Application Platform Engineer / MLOps to join our client, a leading American digital content platform with millions of users and a massive library of ebooks, audiobooks, and documents.
You’ll be working at the intersection of ML Engineering, Infrastructure, and Software Engineering to build scalable and efficient model deployment pipelines, internal tooling, and automation workflows.
This is a long-term, fully remote opportunity with a supportive international team and plenty of room for ownership.

About the project

Client is an American e-book and audiobook subscription service that includes one million titles. The platform hosts 60 million documents on its open publishing platform.
Core Platform provides robust and foundational software, increasing operational excellence to scale apps and data. As a Backend Engineer, your focus will be on building and optimizing scalable backend systems and data pipelines that support real-time processing and event-driven architectures.
Tech Stack: Terraform, Python, Ruby, Go, AWS Sagemaker, Apache Spark (Python/Scala), Jenkins Pipelines, Bash.

Must-have for the position

• 4–5+ years of experience as a software/infrastructure engineer
• Strong hands-on experience with Python and Terraform
• Solid understanding of algorithms and data structures
• Experience operating across ML, infrastructure, and software engineering disciplines
• Bachelor’s degree in Computer Science or equivalent practical experience.
• Strong communication skills and a collaborative mindset.
• Excellent English skills and the ability to engage with both technical and non-technical stakeholders.

Will be a strong plus

• Experience in Scala or Ruby (language polyglots are highly welcome)
• Understanding of how ML models are trained
• Scripting with Bash/Python
• GitHub Actions pipelines
• Experience with AWS Sagemaker
• Interest in trying to work with Go

Responsibilities

• Operate at the intersection of ML Engineering, Infrastructure Engineering, and Software Engineering
• Build and maintain model deployment and monitoring pipelines (AWS Sagemaker)
• Create and maintain client libraries used by internal ML teams
• Manage cloud infrastructure with Terraform
• Write production-ready scripts in Python, or Bash
• Provide guidance to ML engineers on model deployment and operations
• Maintain clean and clear internal documentation and runbooks

IT Craft invites an AI/ML Python Developer to join the company.

Requirements:

• Core Software Engineering: 5 + years Python 3.x; strong proficiency with FastAPI, Django or Flask; Git, unit testing, CI/CD, Docker;
• Generative AI & LLMs: Practical knowledge of leading models (GPT, Claude, Gemini, Mistral, Llama, Qwen, etc); working with them via public APIs, self-hosting or managed platforms (AWS Bedrock, Azure OpenAI, GCP Vertex);
• LLM Techniques: Retrieval-Augmented Generation (RAG), Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (LoRA/QLoRA/PEFT), Reinforcement Learning from Human Feedback (RLHF), prompt engineering and evaluation;
• Chatbots & Agents: Designing multi-turn conversational flows, tool invocation, agent routing/orchestration with LangChain, LlamaIndex, CrewAI, Semantic Kernel or similar;
• Vector Databases: Experience with FAISS, Milvus, Pinecone, Weaviate, Chroma, pgvector (indexing, similarity search, hybrid search);
• MCP Servers: Building and integrating Model Context Protocol (MCP) servers to securely expose domain tools/functions to LLMs;
• Automation Platforms: Advanced use of no-/low-code tools: n8n, Make (Integromat), Zapier (triggers, webhooks, custom modules);
• Soft Skills: Ownership mindset, rapid prototyping, clear technical writing; English at Upper-Intermediate (B2) or higher.

Key Responsibilities:

• Design & build end-to-end LLM workflows in Python (FastAPI, Django or Flask) — from data ingestion to inference APIs;
• Develop and fine-tune models (SFT, LoRA/QLoRA, RLHF) using PyTorch and modern open-source tooling;
• Implement RAG pipelines: document parsing, embedding generation, vector search and evaluation;
• Create chatbots / autonomous agents with frameworks such as LangChain, LlamaIndex, Semantic Kernel or CrewAI;
• Expose tools via MCP servers so that external LLMs can invoke domain-specific actions;
• Integrate no-/low-code automation (n8n, Make, Zapier) to orchestrate business workflows;
• Write clean, test-driven code; set up CI/CD; monitor, log, and continuously improve model performance and system reliability.

Nice to Have:

• Experience with data privacy & compliance (GDPR, SOC 2);
• Operate in cloud & on-prem (Docker, GPU instances, AWS Bedrock/Azure OpenAI, self-hosted LLMs, etc.);
• Hands-on experience with TensorFlow, PyTorch, NumPy, Pandas; ability to train, fine-tune, and evaluate ML/LLM models;
• Familiarity with front-end stacks (React/Next.js, TypeScript) for building AI-powered user interfaces;
• Bonus: Experience in Generative Graphics, including Stable Diffusion, Inpainting techniques, and ControlNets;
• Bonus: Experience in LLM hosting and working with llama.cpp.

Обов’язки:

• Аналіз даних: Збір, обробка та аналіз великих наборів даних для виявлення патернів, трендів та корисної інформації.
• Створення моделей: Розробка, налагодження та впровадження машинних навчальних моделей для прогнозування та класифікації.
• Візуалізація даних: Створення графіків для візуалізації результатів аналізу.
• Співпраця з командами: Робота з командами розробників та продактів для інтеграції моделей у продукти.
• Виконання досліджень: Участь у дослідженнях для вдосконалення існуючих рішень і впровадження нових підходів.
• Документація: Оформлення документації для моделей та процесів аналізу даних.

Вимоги:

• Освіта: Вища освіта у галузі статистики, математики, комп’ютерних наук або в суміжних областях.
• Знання інструментів: Досвід роботи та чудове знання Python та бібліотек для машинного навчання з пріоритетом на табличні дані (Pandas, Numpy, Scikit-learn, Xgboost/LightGBM).
• Математичні навички: Розуміння статистики, теорії ймовірностей та алгоритмів машинного навчання.
• Аналітичні здібності: Вміння аналізувати дані та робити висновки на основі отриманих результатів.
• Комунікаційні навички: Вміння пояснювати технічні концепції нефахівцям і працювати в команді.
• Досвід з SQL: Вміння працювати з базами даних та виконувати запити для отримання інформації.
• Досвід з реальними NLP та Recommender System проектами буде плюсом
• Бекграунд в аналітичній сфері буде плюсом

Our client develops a unique in-memory platform using innovative Machine Learning technologies. The product aims to help businesses’ achieve data and analytics processing needs with the highest speed, and to deliver real-time performance by reproducing companies’ data to the in-memory data store. An impressively fast-growing company that partners with the most leading enterprises from all over the world within various industries including healthcare, telecommunications, retail, etc.
We’re looking for a skilled Data Scientist with a focus on AI data to power the next generation of intelligent solutions. This role is perfect for someone who thrives on tackling complex challenges through machine learning, advanced analytics, and coding, and who’s eager to drive innovation through cutting-edge AI methodologies.

Responsibilities

• Semantic Modeling: Design and maintain semantic representations (e.g., ontologies, entity relationships) to enhance structured data queryability and AI-driven reasoning
• Natural Language to Structured Query Mapping: Design and evaluate approaches that interpret natural language questions and accurately map them to structured data queries (e.g., SQL or semantic equivalents)
• Data-to-Text Interpretation: Design and evaluate techniques for interpreting tabular data and generating human-readable natural language explanations
• LLM Prompt Strategy: Assist in developing and refining prompt engineering strategies to ensure accurate, interpretable, and relevant responses from large language models
• AI Algorithm Development: Design and implement AI algorithms that optimize key system processes and improve overall product performance
• Model Evaluation and Enhancement: Continuously evaluate, refine, and improve existing AI models and algorithms to enhance accuracy, scalability, and computational efficiency
• Research & Innovation: Stay current on advancements in AI, GenAI, NLP, and machine learning, incorporating promising techniques and ideas into product solutions
• Ethics & Compliance: Ensure all model development follows data privacy, governance, and ethical AI standards throughout the lifecycle

Requirements

• Master’s degree in Computer Science, Data Science or Applied Mathematics is required; a Ph.D. is strongly preferred
• 8+ years of experience in Data Science, with hands-on work in NLP, GenAI, and large-scale AI model development
• Strong problem-solving skills and the ability to translate complex business requirements into AI research tasks and deliverables
• Excellent communication skills (English), both verbal and written, with the ability to convey complex technical concepts to cross-functional teams
• Technical Expertise
  • Proven track record in applying data science, machine learning, and AI methodologies in real-world scenarios
  • Strong MLOps experience to help build, deploy, and maintain machine learning models in production. Familiarity with cloud platforms (e.g., AWS, GCP, Azure)
  • Understanding of model versioning, monitoring, and lifecycle management
  • Proficiency in Python and common AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, Langchain, Langgraph)
  • Solid understanding of LLMs, RAG architectures, GraphRAG, techniques to extract knowledge from structured and unstructured data
  • Experience with Agentic workflows and Agentic system design, Orchestration of LLM-powered agents
• Research Execution
  • Ability to define research goals, design experiments, analyze results, and iterate independently and collaboratively
  • Publications or accepted papers in top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR) in areas related to Generative AI
  • Strong performance in GenAI competitions (e.g., Hugging Face Open LLM Leaderboard, AIcrowd, EvalHack, etc.)
  • Participation in leading GenAI hackathons or innovation challenges (e.g., OpenAI, Hugging Face, Google, Anthropic-sponsored)
  • Top rankings or meaningful contributions to Kaggle competitions focused on GenAI/NLP
  • Demonstrated ability to rapidly prototype and scale GenAI solutions in applied settings (internal tools, open-source repos, agents, or copilots)

Ми шукаємо талановитого та досвідченого Data Scientist, який працюватиме над рішеннями генеративного штучного інтелекту для різних галузей та сфер використання. Ви будете використовувати свої навички машинного навчання для вирішення нетривіальних бізнес-завдань для клієнтів EPAM, які бажають використовувати останні досягнення в галузі Data Science та машинного навчання, застосовуючи їх до текстів, зображень, відео та інших даних. Ви працюватимете з крос-функціональними командами інженерів, науковців, продакт-менеджерів, будучи ключовою частиною просування генеративного ШІ від ідеї до реалізації.

Чим ви будете займатися у цій ролі

• Бути лідером в генеративному ШІ та визначати для яких бізнес сценаріїв генеративний ШІ може бути ефективно застосований
• Досліджувати, розробляти та створювати прототипи новітніх підходів до генеративного ШІ, проводити оцінку можливості використання, досліджувати існуючі наукові роботи, впроваджувати та перевіряти його для реальних випадків використання
• Тісно співпрацювати з командою ML engineering на всіх етапах (від досліджень до імплементації генеративного ШІ)
• Співпрацювати з продакт-менеджерами та іншими зацікавленими сторонами бізнесу, щоб сформувати чітке бачення технології та її реальних можливостей
• Презентувати свій результат зацікавленим сторонам і чітко комунікувати як технічну, так і бізнес-частину рішення

Навички

• 5+ років досвіду в Data Science із застосуванням до розробки генеративних моделей (LLMs, GANs, VAE, Diffusion models)
• Досвід роботи з Computer vision, Natural Language Processing problems, досвід роботи з мультимодальними даними (зображення, тексти, аудіо, інші дані)
• Досвід використання Open AI GPTx, досвід дотренування
• Досвід написання готового до впровадження коду з використанням кращих інженерних практик
• Навички програмування на Рython
• Навички роботи принаймні з одним із поширених фреймворків глибинного навчання, таких як Pytorch, Tensorflow тощо
• Досвід оптимізації виробництва моделей глибинного навчання
• Досвід роботи принаймні з однією хмарною платформою (AWS, Azure, GCP)
• Відмінні комунікативні навички
• Знання письмової та усної англійської мови на рівні Upper-Intermediate і вище (В2+)

The primary goal of this initiative is to design and deploy a cloud-based Generative AI system. This advanced solution is tailored to significantly enhance code documentation processes in alignment with the European Railway Traffic Management System (ERTMS) standards. By leveraging the capabilities of Generative AI, the system aims to substantially improve the readability and accuracy of code documentation, ensuring it is comprehensive, easily understandable, and meticulously annotated.

Requirements

• 3+ years of hands on experience with AI (NLP, LLM)
• Strong understanding of prompt engineering techniques
• Strong programming skills in Python
• Experience in scikit-learn, pandas, scipy
• Experience with Python backend is a plus (flask/FastAPI/falcon).
• Familiarity with Langchain or similar frameworks
• Familiarity with use of OpenAI API or similar
• Experience in deploying and managing ML models at scale
• Excellent communication and presentation skills
• Passionate about learning and experimenting with new technologies

Nice to have

• PhD in Computer Science or equivalent industry experience
• MS Azure certification
• Contributor to Open Source Projects

Job responsibilities

As a AI/ML developer, you will contribute to innovative Gen-AI Solutions. Your role will be focused on the early adoption of Generative AI best practices to improve the development life of industrial projects with enhanced Verification and validation cycles and improved Agile methodologies.
Key Responsibilities

• Close collaboration with cross-functional Engineering and Leadership teams to build and integrate Gen-AI frameworks for improved engineering excellence and knowledge-sharing practices
• Research, prototype, benchmark, deploy and maintain AI-driven agents/chatbots
• Implement and validate various use cases and scenarios by AI-assistents and tools
• Integrate various NLP/LLM tools and frameworks with AI-agents
• Integrate MS Azure AI services
• Ensure high-quality deliverables and deployments are provided for Customer teams in order to address AI-driven assistance for SDLC

We’re seeking an MLOps Engineer to join AI projects involving machine learning infrastructure, pipeline development, and modern cloud-native tooling. You’ll work with AWS SageMaker, Bedrock, and related services to automate model training, deployment, and monitoring — while optionally supporting data engineering workflows and cloud infrastructure design.
Depending on the project, your tasks will range from building robust ML pipelines to supporting LLM-based analytics agents with real-time data.

Responsibilities:

• Build and maintain MLOps pipelines using Amazon SageMaker (training, evaluation, inference);
• Integrate with CI/CD systems (e.g., CodePipeline, CodeBuild) to deploy models and pipelines;
• Configure monitoring for data/model drift using SageMaker Model Monitor and CloudWatch;
• Collaborate with data scientists and engineers on training, tuning, and deployment workflows;
• Apply ML experiment tracking (e.g., SageMaker Experiments or MLflow);
• Assist with guardrails and quality checks in LLM-integrated applications;
• Document processes, troubleshoot issues, and participate in sprint planning sessions.

Required skills:

• 2-4 years of experience in MLOps, ML engineering, or cloud-based ML deployment;
• Hands-on experience with AWS SageMaker and core MLOps tools;
• Strong Python skills, especially around ML and automation;
• Familiarity with CI/CD practices in cloud environments;
• Understanding of model lifecycle management (training → deployment → monitoring).

Nice to have:

• Experience with data pipeline tools: Amazon EMR, Glue, Athena, Spark;
• Exposure to LLM services (e.g., AWS Bedrock) and vector search solutions;
• Knowledge of Airflow, feature stores, and API-based agent interfaces;
• Infrastructure-as-Code experience (e.g., CloudFormation, Terraform);
• Familiarity with Salesforce or similar data source integrations.

As Preply scales its AI-powered learning platform, we’re looking for an experienced Senior ML Engineer to help productionize machine learning systems with high reliability, performance, and observability. You’ll work at the intersection of ML, data engineering, and cloud infrastructure enabling fast, secure, and reproducible model development from training to deployment.
You’ll collaborate closely with ML Scientists, Backend Engineers, and Data Engineers to shape the foundations of our ML lifecycle.

What you’ll be doing

• Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton
• Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., spot/GPU autoscaling)
• Define and implement observability and alerting for ML systems (model drift, data quality, feature coverage, etc.)
• Design and scale data ingestion and feature transformation flows using batch (e.g., Spark/BigQuery) and streaming (Kafka or equivalent)
• Contribute to internal Python libraries and platform tooling that accelerate experimentation and deployment for all model teams
• Ensure ML services are modular, testable, and monitored from day one
• Exploration and productionization of LLM-based features (e.g., retrieval pipelines, prompt evaluation, model serving)

What we’re looking for

• Proven experience designing and deploying ML systems in production (5+ years in relevant roles)
• Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.)
• Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows
• Understanding of ML model lifecycles: training, validation, deployment, and monitoring
• Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s)
• Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Product impact driven.
• Exposure to LLM serving, vector databases, or GenAI-powered product flows