EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Description
You are strategic, resilient, engaging with people and a natural self-starter. You have a passion for solving complex problems. If this sounds like you, this could be the perfect opportunity to join EPAM as a Lead Machine Learning Engineer. Scroll down to learn more about the position's responsibilities and requirements.
Req. #306882758
WHAT YOU'LL DO

• Responsible for the transition of machine learning algorithms to production environment and integration with enterprise ecosystem
• Design, create, maintain, troubleshoot, and optimize the complete end-to-end machine learning life cycle, which includes
• machine-learning model optimization
• data preparation
• feature extraction
• model performance monitoring
• AB/Canar/Bluegreen/etc. testing
• Integration with Enterprise ecosystem/IoT devices/Mobile devices
• Write specifications, documentation, and user guides for developed solutions
• Build frameworks for data scientists to accelerate the development of production-grade machine learning models
• Collaborate with data scientists and engineering team to optimize the performance of ML pipeline
• Aid In improvement of SDLC practices
• Exploration of new tools and techniques and propose improvements
• Establish and configure CI/CD/CT processes
• Design and maintain ML models continuous training
• Provide capabilities for early detection of various drifts (data, concept, schema., etc.)
• Continuously identify technical risks and gaps, devise mitigation strategies
• Identify and eliminate technical debt in machine learning systems

REQUIREMENTS

• Experience in Enterprise Software Development for 5+ years
• Solid background in Machine Learning for 3+ Years
• Experience with designing, building and deploying production applications and data pipelines
• Experience in development of highly available, largely scalable, ML driven applications and systems
• Experience with cloud native services: GCP, AWS, Azure
• Able to work closely with customers and other stakeholders
• Strong knowledge and experience in Python development
• Deep understanding of Python ML ecosystem (pytorch, tensorflow, numpy, pandas, sklearn, XGBoost)
• Hands-on experience in implementation of Data Products
• Deep understanding of data preparation and feature engineering
• Understanding of Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
• Deep hands-on experience with implementation of SDLC best practices in complex IT projects
• Experience with automated data pipeline and workflow management tools (Airflow)
• Knowledge and experience in computer science disciplines such as data structures, algorithms, and software design patterns
• Hands-on experience in different data processing paradigms (batch, micro-batch, streaming)
• Deep understanding of MLOps concepts and best practices
• Experience with some of the MLOps related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI / AI Platform, Databricks MLFlow, Kubeflow, Airflow, Argo Workflow, TensorFlow Extended (TFX), etc
• Production experience in integrating ML models into complex data-driven systems/IoT device/Mobile devices
• Experience with basic software engineering tools (CI/CD environments such as Jenkins or Buildkit, PyPi, Docker, Kubernetes)
• Experience with one of the infrastructures as a code (IoC) framework (Terraform/CDK TF, Ansible, AWS CloudFormation / AWS CDK)

BENEFITS

• Medical, Dental and Vision Insurance (Subsidized)
• Health Savings Account
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Short-Term and Long-Term Disability (Company Provided)
• Life and AD&D Insurance (Company Provided)
• Employee Assistance Program
• Unlimited access to LinkedIn learning solutions
• Matched 401(k) Retirement Savings Plan
• Paid Time Off
• Legal Plan and Identity Theft Protection
• Accident Insurance
• Employee Discounts
• Pet Insurance

ADDITIONAL

• Depending on the position, EPAM employees may need to work at a client worksite or an EPAM office. To protect employees and help communities fight the COVID-19 pandemic, vaccination is required to visit an EPAM office in the US, and many of our clients have similar policies in place. Due to this, a COVID-19 vaccination may be necessary and when applicable, specific details will be discussed during the interview process which may include providing proof of vaccination. For candidates with exceptional circumstances that prevent them from getting the COVID-19 vaccine, we will offer alternative reasonable accommodation, where possible, which should be coordinated by your recruiter and discussed directly with an HR Representative
• This position operates in a remote capacity, but you must live within driving distance to an EPAM office. Your recruiter will discuss specific details about work location during the initial interview process