Lead MLOps Engineer
4 weeks ago
Description
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.
We are seeking an experienced Lead MLOps Engineer, expertise in machine learning operations. The ideal candidate will play a key role in strategizing, planning, and implementing MLOps initiatives, working closely with business stakeholders and leading a team of junior and senior ML engineers. The candidate should have a strong background in designing, developing, and deploying complex AI/ML solutions on cloud infrastructure.
#LI-DNI #REF-IN-WOMEN
Responsibilities
Strategise, plan and deliver MLOps initiatives by liasing with key business stakeholders Design, develop and deploy complex AI/ML solutions on cloud infrastructure (using ML engineering, ML Ops workflows & tools) that can scale in response to changing business and technical requirements Create infra and architecture diagrams Ability to project manage, allocate activties to junior ML engineers and take it to closure Improvise coding practices, support code reviews and bring in best practices for model management Provide thought leadership in terms of new technologies and tools, suggest improvements Able to support in the interview process to hire junior and senior ML engineers
Requirements
Minimum of 9 years of hands-on experience in MLOps with a focus on deploying AI/ML solutions Proven project management skills, with the ability to lead and coordinate activities within a team Excellent communication and collaboration skills Experience with ML engineering, model management, and supporting code reviews Demonstrated ability to provide thought leadership and drive innovation in MLOps processes
We offer
Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Unlimited access to LinkedIn learning solutions Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: Health benefits Retirement benefits Paid time off Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)
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