Offer summary

Qualifications:

6+ years of experience in software engineering, Proficiency in Python for automation scripts and tools, Hands-on experience with AWS services, especially Lambda and API Gateway, In-depth knowledge of Databricks, including MLflow and Lakehouse architecture..

Key responsibilities:

Develop and implement automation for model promotion workflows using Databricks and MLflow.

Design and deploy scalable model serving solutions leveraging Databricks and AWS services.

Establish monitoring systems for the Databricks Lakehouse to ensure data quality and model performance.

Collaborate with cross-functional teams to integrate MLOps solutions into existing infrastructure.

Job description

About us:

At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.

About the Client:

Join one of the Fortune 500 leaders in the pharmaceutical industry that is looking innovate and expand our technological capabilities. The person would join a product team working on their self-service company-wide platform that enables all the teams and business units to deploy their AI solutions, making them accessible across the entire company.

Position Summary:

We are seeking a skilled Software Engineer to lead the development of MLOps automation solutions within the Databricks platform. This role is pivotal in enhancing our machine learning operations by integrating robust automation processes.

The role is a CONTRACTING (6 months and renewable) role with US company.

Accepting canddiates from Europe, Middle East and India, who can overlap IST working hours.

Accepting candidates that can be available to start by July 1st.

No agency candidates accepted.

Key Responsibilities:

Develop and implement automation for model promotion workflows using Databricks Model Registry and MLflow.
Design and deploy scalable model serving solutions leveraging Databricks Model Serving and AWS services.
Establish comprehensive monitoring systems for the Databricks Lakehouse to ensure data quality and model performance.
Automate Databricks workflows for efficient execution of notebooks, scripts, and ML pipelines.
Utilize AWS Lambda and API Gateway to create event-driven architectures that trigger Databricks jobs and manage model endpoints.
Collaborate with cross-functional teams to integrate MLOps solutions seamlessly into existing infrastructure

Requirements

6+ years of experience in software enigneering
Proficiency in Python, with a strong background in developing automation scripts and tools.
Hands-on experience with AWS services, particularly Lambda and API Gateway, for building serverless applications.
In-depth knowledge of Databricks, including experience with MLflow, Model Serving, and Lakehouse architecture.
Familiarity with MLOps practices and tools for continuous integration and deployment of machine learning models.
Experience in setting up monitoring and alerting systems for data pipelines and ML models

Required profile