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Machine Learning Engineer

72% Flex
Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

Proven experience in designing and implementing machine learning models and algorithms, Proficiency in developing scalable machine learning pipelines with Apache Spark and Databricks, Skilled in implementing MLOps practices for efficient model deployment and monitoring, Experience leveraging Microsoft Azure for cloud-based machine learning solutions, Ability to collaborate effectively with data scientists and other stakeholders to understand and meet business needs, Expertise in evaluating and optimizing machine learning models for performance and accuracy.

Key responsabilities:

  • Design and implement machine learning models and algorithms
  • Develop scalable machine learning pipelines using Apache Spark and Databricks
  • Implement MLOps practices to ensure efficient model deployment and monitoring
  • Utilize Microsoft Azure for cloud-based machine learning services
  • Collaborate with data scientists and other stakeholders to align with business requirements
  • Evaluate and optimize machine learning models for enhanced performance and accuracy
EPAM Systems logo
EPAM Systems Information Technology & Services XLarge https://www.epam.com/
10001 Employees
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Job description

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Your missions


Description

Join our innovative team as a Machine Learning Engineer and contribute to our groundbreaking GenAI project.

In this role, you will develop and implement advanced machine learning models and algorithms to revolutionize customer experiences, optimize business operations, and significantly boost revenue growth.

You will be instrumental in designing scalable machine learning pipelines and deploying models effectively to achieve strategic project objectives.

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.

Responsibilities

  • Design and implement machine learning models and algorithms
  • Develop scalable machine learning pipelines using Apache Spark and Databricks
  • Implement MLOps practices to ensure efficient model deployment and monitoring
  • Utilize Microsoft Azure for cloud-based machine learning services
  • Collaborate with data scientists and other stakeholders to align with business requirements
  • Evaluate and optimize machine learning models for enhanced performance and accuracy


Requirements

  • Proven experience in designing and implementing machine learning models and algorithms
  • Proficiency in developing scalable machine learning pipelines with Apache Spark and Databricks
  • Skilled in implementing MLOps practices for efficient model deployment and monitoring
  • Experience leveraging Microsoft Azure for cloud-based machine learning solutions
  • Ability to collaborate effectively with data scientists and other stakeholders to understand and meet business needs
  • Expertise in evaluating and optimizing machine learning models for performance and accuracy


Nice to Have

  • Experience in customer-focused projects or the retail industry
  • Familiarity with GenAI technologies and applications
  • Strong problem-solving skills and attention to detail


Technologies

  • Apache Spark
  • Databricks
  • Microsoft Azure
  • Python


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


Conditions

  • 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




EPAM Systems is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, status as a qualified individual with disability, or any other protected characteristic under law.

Background investigations are required for all new hires as a condition of employment, after the job offer is made. Employment will not begin until EPAM Systems receives and approves the results of the background check.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Soft Skills

  • open-mindset
  • verbal-communication-skills
  • collaboration

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