MLOps Lead Engineer IRC283110

Description

Model Deployment and Operations:

Deploy, monitor, and maintain machine learning models in production environments.

Automate model training, retraining, versioning, and governance processes.

Monitor model performance, detect drift, and ensure scalability and reliability of ML workflows

Infrastructure and Pipeline Management:

Design and implement scalable MLOps pipelines for data ingestion, transformation, and model deployment.

Build infrastructure-as-code solutions using tools like Terraform to manage cloud environments (AWS, GCP)

Collaboration with Teams:

Work closely with data scientists to operationalize machine learning models.

Collaborate with software engineers to integrate ML systems into broader platforms

Cloud and Big Data Expertise:

Utilize cloud services from AWS, GCP, and Snowflake for scalable data storage and processing.

DevOps Integration:

Implement CI/CD pipelines and automations to streamline ML model deployment.

Use containerization tools like Docker and orchestration platforms like Kubernetes for scalable deployments

Use Observability platforms to monitor pipeline and operational health of model production, delivery and execution

Requirements

Technical Skills:

Proficiency in Python for ML development; familiarity with additional languages like Clojure is a plus.

Expertise in cloud platforms (AWS, GCP) and data warehouses like Snowflake or BigQuery.

Strong knowledge of MLOps frameworks (e.g., Kubeflow, MLflow) and DevOps tools (e.g., Jenkins, GitLab, Flux)

Experience with containerization (Docker) and orchestration (Kubernetes)

Experience with infrastructure-as-code tools like Terraform

Machine Learning Knowledge:

Solid understanding of machine learning principles, including model evaluation, explainability, and retraining workflows.

Hands-on experience with ML frameworks such as TensorFlow or PyTorch

Big Data Handling:

Proficiency in SQL/NoSQL databases and distributed computing systems like Dataprov, EMR, Spark, Hadoop

Soft Skills:

Strong communication skills to collaborate across multidisciplinary teams.

Problem-solving mindset with the ability to work in agile environments

Experience:

At least 5+ years in platform, software, or MLOps engineering roles

Proven track record of deploying scalable ML solutions in production environments

Job responsibilities

 

Model Deployment and Operations:

Deploy, monitor, and maintain machine learning models in production environments.

Automate model training, retraining, versioning, and governance processes.

Monitor model performance, detect drift, and ensure scalability and reliability of ML workflows

Infrastructure and Pipeline Management:

Design and implement scalable MLOps pipelines for data ingestion, transformation, and model deployment.

Build infrastructure-as-code solutions using tools like Terraform to manage cloud environments (AWS, GCP)

Collaboration with Teams:

Work closely with data scientists to operationalize machine learning models.

Collaborate with software engineers to integrate ML systems into broader platforms

Cloud and Big Data Expertise:

Utilize cloud services from AWS, GCP, and Snowflake for scalable data storage and processing.

DevOps Integration:

Implement CI/CD pipelines and automations to streamline ML model deployment.

Use containerization tools like Docker and orchestration platforms like Kubernetes for scalable deployments

Use Observability platforms to monitor pipeline and operational health of model production, delivery and execution

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.