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Middle/Senior ML Engineer

extra holidays - extra parental leave
Remote: 
Full Remote
Experience: 
Senior (5-10 years)

Offer summary

Qualifications:

Strong understanding of ML algorithms and math, Experience with AWS, Python, and Docker, Background in production-level ML models, Familiarity with NLP, LLMs, and recommendation engines, Ability to produce structured software modules.

Key responsabilities:

  • Develop and enhance ML models
  • Collaborate with cross-functional teams
  • Create reproducible experimentation environment
  • Monitor and optimize ML models in production
  • Stay updated on ML/AI trends
Provectus logo
Provectus Information Technology & Services SME https://www.provectus.com/
501 - 1000 Employees
See more Provectus offers

Job description

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!

Requirements:
  • Comfortable with standard ML algorithms and underlying math.
  • Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
  • AWS Bedrock experience strongly preferred
  • Practical experience with solving classification and regression tasks in general, feature engineering.
  • Practical experience with ML models in production.
  • Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
  • Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
  • Python expertise, Docker.
  • English level - strong Intermediate.
  • Excellent communication and problem-solving skills.

  • Will be a plus:
  • Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
  • Practical experience with deep learning models.
  • Experience with taxonomies or ontologies.
  • Practical experience with machine learning pipelines to orchestrate complicated workflows.
  • Practical experience with Spark/Dask, Great Expectations.

  • Responsibilities:
  • Create ML models from scratch or improve existing models. 
  • Collaborate with the engineering team, data scientists, and product managers on production models.
  • Develop experimentation roadmap. 
  • Set up a reproducible experimentation environment and maintain experimentation pipelines.
  • Monitor and maintain ML models in production to ensure optimal performance.
  • Write clear and comprehensive documentation for ML models, processes, and pipelines.
  • Stay updated with the latest developments in ML and AI and propose innovative solutions.
  • Required profile

    Experience

    Level of experience: Senior (5-10 years)
    Industry :
    Information Technology & Services
    Spoken language(s):
    English
    Check out the description to know which languages are mandatory.

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