[Hiring] Senior Data Scientist @Automat-it

Role Description

We’re looking for a Senior Data Scientist to join our Data Science practice and work directly with customers on complex AI and Machine Learning projects on AWS. This is not a traditional analytics or research-focused Data Science role. You’ll work across classical ML, fine-tuning, GenAI, multimodal systems, and production ML on AWS, helping customers decide which technical approach actually fits their problem.

You’ll own projects end-to-end: understand the customer’s domain and data, evaluate different solution paths, define the architecture, implement the critical parts, and guide delivery through production.

📍 Work location: remote from Ukraine

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

Key Responsibilities

• Own Data Science projects end-to-end: Take customer problems from technical discovery through data analysis, solution design, experimentation, implementation, deployment, and production validation.
• Choose the right technical approach: Evaluate whether a problem should be solved with prompt engineering, RAG, GenAI, agentic workflows, fine-tuning, smaller language models, classical ML, Computer Vision, recommendation systems, or custom model training.
• Work deeply with data: Analyze and prepare customer datasets, identify data quality issues, create representative validation and golden datasets, and ensure the available data can support the chosen modelling approach.
• Build and fine-tune ML models: Train, fine-tune, optimize, evaluate, and deploy models using Python, PyTorch/TensorFlow, SageMaker, and modern ML tooling.
• Work with Generative AI: Build and evaluate GenAI solutions using Amazon Bedrock, RAG, prompt engineering, model selection, agentic workflows, and related AWS-native AI services.
• Use SageMaker in production: Work with SageMaker Studio, training jobs, endpoints, pipelines, model registry, batch inference, monitoring, and other production ML capabilities.
• Design production-ready solutions: Make architecture decisions across quality, latency, cost, scalability, maintainability, observability, and operational complexity.
• Work directly with customers: Participate in technical discovery, workshops, architecture discussions, and delivery conversations with founders, CTOs, engineering teams, and technical stakeholders.
• Challenge technical assumptions: Help customers avoid unnecessary complexity, explain trade-offs, costs and recommend simpler or more effective approaches when appropriate.
• Lead through technical ownership: Independently own projects with minimal supervision and mentor less experienced Data Scientists and engineers when needed.
• Collaborate across teams: Work closely with AI Engineers, MLOps, Data Engineering, DevOps, and Solution Architecture teams on customer solutions that cross multiple technical domains.

Qualifications

• 5+ years of experience in Data Science, Machine Learning, Applied Science, or a closely related role.
• Strong classical Machine Learning fundamentals and hands-on experience building production ML solutions.
• Deep practical experience working with data, including data preparation, validation, feature engineering, dataset construction, and model evaluation.
• Strong Python skills and hands-on experience with PyTorch and/or TensorFlow.
• Strong practical experience with AWS SageMaker beyond notebook-level usage, including model training, deployment, inference, pipelines, or production operations.
• Hands-on experience with Amazon Bedrock and modern Generative AI approaches.
• Practical experience with fine-tuning models and understanding when fine-tuning is preferable to prompting, RAG, or other approaches.
• Experience in at least one strong ML domain such as NLP, Computer Vision, recommendation systems, forecasting, structured ML, multimodal ML, or similar.
• Understanding of RAG, embeddings, prompt engineering, foundation models, and agentic workflows.
• Strong understanding of MLOps and production ML practices, including model deployment, monitoring, reproducibility, lifecycle management, and CI/CD.
• Experience designing and owning solutions independently rather than working only from predefined technical specifications.
• Strong customer-facing communication skills and ability to explain technical trade-offs clearly.
• Ability to work with ambiguity, messy real-world data, and changing customer requirements.
• Strong technical judgment and a pragmatic approach to balancing model quality with delivery speed, cost, and business value.

Nice to have

• Experience with AgentCore, Bedrock Agents, LangGraph, Strands Agents, or other agentic frameworks.
• Experience with Small Language Models or domain-specific model adaptation.
• Experience with recommendation systems, audio ML, signal processing, or multimodal systems.
• Experience in technical consulting, pre-sales, or customer discovery.
• AWS Machine Learning certifications.
• Master’s degree or PhD in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field.

Why Join Automat-it?

• Be at the Forefront of Cloud Innovation: Join a global leader and AWS Premier Tier Services Partner. We don't just use the cloud; we master it.
• Work on Meaningful, Large-Scale Impact: We specialize in helping startups and scaleups scale at speed.
• Accelerate Your Career Trajectory: Clear progression, continuous learning, and cutting-edge exposure.
• Thrive in a Culture of Excellence: Collaborative, supportive, and transparent culture with mentorship opportunities.
• Global Reach, Boutique Feel: Enjoy the stability of a mature, profitable company with the agility and spirit of a startup.

Company Description

Automat-it is committed to fostering a workplace that promotes equal opportunities for all. We firmly believe that cultivating a diverse workforce is crucial to our success. Our recruitment decisions are grounded in your experience and skills, recognizing the value you bring to our team.