ML Engineer

Arrise Solutions (India) Pvt. Ltd.; Hyderabad; Remote; INR 1,200,000 - 2,500,000; Full time

Job summary

Arrise Solutions (India) Pvt. Ltd. seeks an ML Engineer to join a global data science team. Based in Hyderabad, Noida, or remote, you will design, develop, and maintain ML pipelines and manage model experimentation and deployment.

You will optimize models for latency and throughput, build CI/CD pipelines, containerize applications, and monitor production ML systems. Collaboration across data and engineering teams will drive advanced MLOps practices.

Qualifications

• Degree in CS/Engineering or related field.
• Strong Python programming and ML framework experience.
• Experience with ML lifecycle tools and experiment tracking.
• Background in deploying and monitoring ML models at scale.
• Familiarity with CI/CD and containerization practices.

Responsibilities

• Design, develop, and maintain ML pipelines for production.
• Implement scalable ML infrastructure for diverse data types.
• Optimize models for latency, memory, and throughput.
• Develop CI/CD pipelines and containerize production apps.
• Monitor production ML systems and troubleshoot issues.
• Collaborate with cross-functional teams to solve problems.
• Lead research on new ML/MLOps methodologies.

Skills

Python

PyTorch

TensorFlow

MLflow

DVC

LakeFS

Git

CI/CD

Docker

MLOps

Model deployment

Monitoring

Communication

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

MLflow

DVC

LakeFS

Git

GitLab CI/Jenkins

Docker

Grafana

Job description

About the Role

The ML Engineer works within a global team of Data Scientists, delivering machine learning methods into production in the most efficient way possible. This role designs, develops, and maintains ML pipelines, implements monitoring and alert systems, and optimizes trained AI models for latency, memory, and throughput. Based in Hyderabad, Noida, or remote, the ideal candidate has in-depth knowledge of model management, experiment tracking, and MLOps practices.

Key Responsibilities

• Design, develop, and maintain ML pipelines, ensuring high reliability and scalability.
• Implement scalable machine learning infrastructure to deploy algorithms based on image, text, audio, and tabular data.
• Optimize trained AI models for latency, memory, and throughput.
• Develop CI/CD pipelines and containerize production applications.
• Automate existing workflows within the Data Science team.
• Monitor and troubleshoot production ML systems using alert systems.
• Collaborate with cross-functional teams across data and engineering to solve complex problem statements.
• Lead research initiatives to explore new methodologies and contribute to best MLOps practices.

Key Skills

• 2-5 years of experience, with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Strong proficiency in Python, with extensive experience in PyTorch or TensorFlow.
• Extensive knowledge of key machine learning metrics and optimization techniques.
• Strong knowledge of version control systems (Git, data versioning).
• Experience with model management and experiment tracking frameworks (e.g., MLflow, DVC, LakeFS).
• Strong knowledge and practical understanding of MLOps techniques.
• Prior experience deploying and monitoring scalable ML models, CI/CD pipelines, and containerization.
• Excellent problem-solving, analytical, and communication skills.

Good to Have

• Extensive experience with the Azure ecosystem, particularly Azure Machine Learning.
• Experience developing computer vision, text, audio, or tabular data models.
• Strong proficiency in Gitlab CI, Jenkins, Grafana, and Docker.
• Excellent software engineering skills in API design and concurrency.