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Machine Learning Engineer - Remote Remote

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Machine Learning Engineer - Remote Description


Are you a passionate machine learning enthusiast with a solid technical foundation? Do you thrive on tackling complex projects that push the boundaries of innovation? If so, we invite you to apply for the role of Machine Learning Engineer.

Client uses advanced AI and machine learning to build technology for legal professionals, creating solutions that help them work more efficiently and provide higher-quality representation to more clients.
As part of the acquisition, the application will evolve with more skills (features), a centralized AI Assistant service will be leveraged Enterprise wide and contribution to the creation of the Generative AI Platform will be made via a common AI skill (feature) creation framework.

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.


  • Develop and implement MLOps methodologies and frameworks
  • Create and maintain machine learning workflows and pipelines
  • Collaborate with data scientists and engineers to build scalable and reliable machine learning models
  • Automate deployment, monitoring, and management of machine learning systems
  • Ensure the integrity, security, and performance of machine learning infrastructure and applications
  • Ensure the integrity, security, and performance of machine learning infrastructure and applications
  • Stay updated with the latest trends and technologies in MLOps and implement best practices


  • Proven experience as a Developer with expertise in MLOps
  • Strong knowledge and understanding of machine learning engineering principles
  • In-depth understanding of MLOps practices and tools
  • Proficiency in programming languages such as Python, Java, or Scala
  • Experience with cloud platforms and containerization technologies
  • Excellent problem-solving and analytical skills
  • Good communication and teamwork abilities

Nice to have

  • Ideally has worked previously with writing or deploying machine learning models for use in a production setting


  • Amazon web services
  • Data Management
  • Dataiku
  • ML Arquitecture
  • Programming paradigms
  • Snowflake

We Offer

  • Career plan and real growth opportunities
  • Unlimited access to LinkedIn learning solutions
  • International Mobility Plan within 25 countries
  • Constant training, mentoring, online corporate courses, eLearning and more
  • English classes with a certified teacher
  • Support for employee’s initiatives (Algorithms club, toastmasters, agile club and more)
  • Enjoyable working environment (Gaming room, napping area, amenities, events, sport teams and more)
  • Flexible work schedule and dress code
  • Collaborate in a multicultural environment and share best practices from around the globe
  • Hired directly by EPAM & 100% under payroll
  • Law benefits (IMSS, INFONAVIT, 25% vacation bonus)
  • Major medical expenses insurance: Life, Major medical expenses with dental & visual coverage (for the employee and direct family members)
  • 13 % employee savings fund, capped to the law limit
  • Grocery coupons
  • 30 days December bonus
  • Employee Stock Purchase Plan
  • 12 vacations days plus 4 floating days
  • Official Mexican holidays, plus 5 extra holidays (Maundry Thursday and Friday, November 2nd, December 24th & 31st)
  • Relocation bonus: transportation, 2 weeks of accommodation for you and your family and more
  • Monthly non-taxable amount for the electricity and internet bills


  • By applying to our role, you are agreeing that your personal data may be used as in set out in EPAM´s Privacy Notice and Policy

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