AI and ML Engineer

Our requirements

• 5+ years of professional experience in machine learning, AI engineering, or related fields.
• Master’s degree in Computer Science, Machine Learning, Physics, or related field; PhD preferred.
• Proficient in Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding of algorithms, statistics, probability, and linear algebra.
• Hands-on experience with data pipelines and ETL tools (e.g., Spark, AWS Lambda, AWS Glue).
• Practical experience with cloud platforms, preferably AWS.
• Solid software engineering fundamentals including version control (Git), testing, and design patterns.
• Demonstrated success in deploying ML models into production at scale.
• Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work autonomously and collaboratively within a fast-paced, cross-functional team environment.

Optional

• Experience with agentic frameworks like LangChain or LangGraph

Your responsibilities

• Design, implement, and optimize machine learning and AI models, including classification, regression, clustering, and agent tuning.
• Experiment with the latest methods, frameworks, and architectures to enhance model performance and efficiency.
• Develop robust, scalable ML pipelines for training, validation, and inference.
• Deploy ML models into production environments (cloud or on-prem), ensuring high reliability, low latency, and scalability.
• Apply MLOps best practices including CI/CD, monitoring, automated retraining, and model registry management.
• Partner with data engineering teams to source, clean, and transform large datasets for model training and inference.
• Ensure high data quality, perform feature engineering, and support real-time data integration processes.
• Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
• Clearly communicate complex technical results to both technical and non-technical stakeholders.
• Provide technical guidance and mentorship to junior ML engineers and data scientists.
• Contribute to establishing team best practices, code reviews, and architectural decisions.

About the project

This is how we organize our work

This is how we work on a project

• code review
• Continuous Deployment
• Continuous Integration
• documentation
• test automation

What we offer

• This is a contract position.

Development opportunities we offer

• development budget
• external training
• intracompany training
• mentoring
• support of IT events
• technical knowledge exchange within the company

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• life insurance
• remote work opportunities
• flexible working time
• corporate products and services at discounted prices
• integration events
• coffee / tea
• drinks
• sharing the costs of tickets to the movies, theater
• employee referral program
• opportunity to obtain permits and licenses
• extra leave

DataArt Poland sp. z o.o.