Senior Machine Learning Engineer

Responsibilities

• Contribute to the design, development, and operational lifecycle of the ML pipeline based on best practices
• Design, create, maintain, troubleshoot, and optimize ML pipeline steps
• Own and contribute to the design and implementation of ML prediction endpoints
• Collaborate with System Engineers to configure the ML lifecycle management environment
• Write specifications, documentation, and user guides for developed applications
• Promote improved coding practices and repository organization in the science work cycle
• Establish and configure pipelines for projects
• Identify technical risks and gaps, and devise mitigation strategies
• Collaborate with data scientists to productionalize predictive models, understand the scope and purpose of the models built by data scientists, and create scalable data preparation pipelines

Requirements

• Minimum of 3 years of programming language experience, ideally in Python, and strong SQL knowledge
• Robust MLOps experience (Sagemaker, Vertex, or Azure ML)
• Intermediate level in Data Science, Data Engineering, and DevOps Engineering
• Experience with at least one project delivered to production in an MLE role
• Expertise in Engineering Best Practices
• Practical experience in implementing Data Products using the Apache Spark Ecosystem (Spark SQL, MLlib/SparkML) or alternative technologies
• Experience with Big Data technologies (e.g., Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc.)
• Proficiency in automated data pipeline and workflow management tools, i.e., Airflow, Argo Workflow, etc
• Experience in different data processing paradigms (batch, micro-batch, streaming)
• Practical experience working with at least one major Cloud Provider such as AWS, GCP, and Azure
• Production experience in integrating ML models into complex data-driven systems
• DS experience with Tensorflow/PyTorch/XGBoost, NumPy, SciPy, Scikit-learn, Pandas, Keras, Spacy, HuggingFace, Transformers
• Experience with different types of databases (Relational, NoSQL, Graph, Document, Columnar, Time Series, etc.)
• Practical experience with LLM for conversational AI systems would be a huge plus

We offer

• Diverse multicultural, multi-functional, and multilingual work environment
• Global scope, international projects in different business domains: life sciences and healthcare, retail, and distribution, software and hi-tech, etc
• Outstanding career development opportunities with a transparent career path and a roadmap to accelerate your journey
• Numerous opportunities for self-development: hard & soft skills internal training courses, mentoring programs, and unlimited access to LinkedIn Learning courses
• Knowledge-sharing with colleagues from EPAM's global tech communities
• English language courses
• 25 days holiday per annum
• 5 days of sick leave without medical certification
• Private health insurance for employees and discount for private health insurance for family members
• Discount for Fit Pass program
• Comfortable modern offices in Belgrade and Novi Sad or remote work from any location in Serbia
• Regular corporate and social events (parties, sport events, advanced CSR programs etc.)
• Learning programs for kids (eKids)