MLOps Team Lead

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client is a company 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, the company delivers hands-on DevOps, FinOps, and GenAI support that drives real results. The company works across EMEA, fueling innovation and solving complex challenges daily.

About the role:
We’re hiring an MLOps Team Lead to join the innovative team. You will lead a group of highly skilled MLOps Engineers, develop robust MLOps pipelines, create cutting-edge Generative AI solutions, effectively engage with customers to grasp their requirements, and oversee project success from inception to completion.

Requirements:
- Proven leadership experience with a track record of managing and developing technical teams.
- Excellent customer-facing skills to understand and address client needs effectively.
- Ability to design and implement cloud solutions and to build MLOps pipelines on AWS.
- Experience with one or more MLOps frameworks like Kubeflow, MLFlow, DataRobot, Airflow, etc.
- Fluency in Python, a good understanding of Linux, and knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
- Ability to understand tools used by data scientists and experience with software development and test automation.
- Experience with one or more large language models, such as frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex.
- Experience with Docker.
- Fluent in written and verbal communication skills in English.

Nice to have:
- Working knowledge of some Vector Databases such as OpenSearch, Qdrant, Weaviate, LanceDB, etc.
- Working knowledge of Snowflake, BigQuery, and/or Databricks.
- GCP or Azure knowledge (DevOps/MLOps).
- ML certification (AWS ML Specialty or similar).

Responsibilities:
- Manage a team of highly professional MLOps Engineers focusing on their growth and execution excellence.
- Lead and be responsible for on-time, great-quality project deliveries.
- Developing MLOps pipelines leveraging the Amazon SageMaker platform and its features.
- Developing Generative AI solutions and POCs, utilizing the latest architectures and technologies.
- Delivering end-to-end ML products - model performance development, training, validation, testing, and version control.
- Provision of ML AWS resources and infrastructure.
- Developing ML-oriented CI/CD pipelines using GitHub Actions, BitBucket, or similar tools.
- Deploying Machine Learning models in production.
- Help customers tackle challenges on a scale using distributed training frameworks.
- Using and writing Terraform libraries for infrastructure deployment.
- Developing CI/CD pipelines for projects of various scales and tech stacks.
- Maintaining infrastructures and environments of all types, from dev to production.
- Security monitoring and administration.

The company offers:
- 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.