Responsibilities

Lead the design and development of data science solutions, including data pipelines and ML processes, leveraging your technical expertise.

Lead and mentor a team of data scientists, providing technical guidance and oversight to ensure high-quality deliverables.

Accurately estimate time and resources required for new projects.

Promote a continuous learning and improvement culture, staying up-to-date with industry best practices and emerging technologies.

Evaluating team performance and providing feedback and coaching.

Encouraging collaboration and open communication within the team and with other stakeholders.

Participating in the recruitment process to select new team members.

Requirements

Strong technical skills in code review, architecture and data models.

Experience designing ML pipelines, including data collection, wrangling, training and validating ML, delivering and serving.

Passion for continuous learning and improvement.

Ability to accurately estimate time and resources for projects.

Ability to manage timelines and deadlines while ensuring high-quality work.

Excellent communication and collaboration skills.

Ability to identify and address performance issues and recognise high performers.

Strong leadership and mentoring skills.

Experience in recruiting and building a team.

Required skills

Minimum English level B2.

6+ years of proven experience developing software using an object-oriented or functional language.

Strong programming skills in Python.

Proficiency in math and ML.

Solid with ML libraries (numpy, pandas, scikit-learn) and frameworks (Pytorch, TensorFlow).

Good at generative ML and most valuable solutions (LLM architectures and current tech stack to work with them, OpenAI API, AWS Bedrock, Google Google Gemini/Gemma).

Good at current CV architectures (ResNet, AE, VAE, U-Net, GAN, Diffusion models).

Experience working with Cloud Platforms (GCP, AWS, Azure – any of the listed) and their data-oriented components.

Experience in ML serving concepts (CI/CD, REST/GRPC, flask/fastapi, docker, docker-compose).

Expertise in the use of any relational databases (e.g., PostgreSQL, MSSQL, MySQL).

A team player with excellent collaboration skills.

Will be a great plus

Expertise in data storage design principles. Understanding of pros and cons of SQL/NoSQL solutions, their types and configurations (standalone/cluster, column/row-oriented, key-value/document stores).

Deep knowledge of Spark internals (tuning, query optimisation, spark ML).

Experience with data integration and business intelligence architecture.

Experience with non-relational databases (e.g., MongoDB, DynamoDB).

Experience with stream processing using the current industry standards (e.g., AWS Kinesis, Kafka streams, etc.).

Experience with containerised (Docker, ECS, Kubernetes) or serverless (Lambda) deployment.

Good knowledge of popular data standards and formats (e.g., JSON, XML, Proto, Parquet, Avro, ORC, etc.).

Experience with any of MLOps framework.

Experience in data science and machine learning with building Machine Learning models.

Experience with text-to-speech and speech-to-text architectures and models.

NIX is a global supplier of software engineering and IT outsourcing services

NIX teams collaborate with partners from different countries. Our specialists have experience in developing innovative projects from ecommerce to cloud for some of the largest companies in the world, including from the Fortune 500. The teams are focused on stable development of the international IT market, business, and their own professional skills.