MLOps + Databricks Engineer

3 weeks ago

india LTIMindtree Full time

LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world.


Job Details-

Location – Mumbai / Pune / Delhi / Chennai / Bangalore / Noida / Kolkata / Coimbatore

Notice Period - Immediate to 60 Days only

Experience - 6+ Yrs

Primary Skills : MLOps and Data Bricks


Job Summary:

Were looking for a ML/MLOps Engineering Specialist who is experienced in designing and implementing ML applications at scale in production for our ML Engineering team. The team is a cross-functional team and has ML Engineers and Software Engineers, and closely works with data scientists and data engineers in designing, building and operationalizing AI/ML models.


Roles and Responsibilities:

  • As a ML Engineering Specialist, you will be a key stakeholder and owning responsibility in designing and architecting end to end ML solutions.
  • Operationalize ML models, NLP, Computer Vision, and other type of models.
  • End to End model lifecycle management, starting from feature extraction to monitor machine learning models using high end tools and technologies.
  • Design & implementation of DevOps principles in Machine Learning
  • Model quality assurance, governance, and monitoring
  • Integrate models as part of business applications via APIs.
  • Execute best practices in version control and continuous integration / delivery.
  • Collaborate with data scientists, engineers, and other key stakeholders.
  • Work well in a fast-paced cross-functional environment


Mandatory Skills/Requirements:

  • Experience in implementing machine learning life cycle on Databricks.
  • Experience with creating ML pipelines using Azure DevOps
  • Experience with Machine learning frameworks, libraries, and agile environments.
  • Experience with various model deployment strategies.
  • Experience with Python and SQL is must. Understanding of distributed frameworks such as Spark, Dask, Ray etc. is a plus.
  • Experience with version control tools such as Git, Bitbucket etc.
  • Knowledge on Docker, Jenkins, Kubernetes, and other DevOps tools.
  • Knowledge on Infra-as-a-Code via ARM or Terraform templates.
  • Familiarity with Large Language Models and Operationalization of foundation models on cloud platforms will be a plus.
  • Outstanding analytical and problem-solving skills

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