4423343-Lead Assistant Manager
EXL · Bengaluru, Karnataka, India
- On site
- Full-time
- ₹1,500,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Lead ML model deployment and management.
- Collaborate with DevOps and data teams.
- Innovate MLOps technologies and processes.
- Build software for ML models.
- Mentor junior team members.
About the role
Machine Learning Engineer Manager
Company: EXL Services
Location: Bangalore/Noida/Pune/Hyderabad/Gurgaon/ WFH Mode
Education: B.E. / B. Tech / M.E. / M. Tech / MCA
Experience Required: 4+ years of relevant experience
Job Responsibilities
- Model Deployment and Management: Drive ML prototypes into production ensuring seamless deployment and management on cloud at scale. Monitor real-time performance of deployed models, analyze data, and proactively address performance issues. Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability.
- Collaboration and Integration: Collaborate with DevOps engineers to manage cloud compute resources for ML model deployment and performance optimization. Work closely with ML scientists, software engineers, data engineers, and other stakeholders to implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated deployment.
- Innovation and Continuous Improvement: Stay updated with the latest advancements in MLOps technologies and recommend new tools and techniques. Contribute to the continuous improvement of team processes and workflows. Share knowledge and expertise to promote a collaborative learning environment.
- Development and Documentation: Build software to run and support machine-learning models. Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes. Participate in fast iteration cycles and adapt to evolving project requirements.
- Business Solutions and Strategy: Propose solutions and strategies to business challenges. Collaborate with Data Science team, Front End Developers, DBA, and DevOps teams to shape architecture and detailed designs.
- Mentorship: Conduct code reviews and mentor junior team members. Foster strong interpersonal skills, excellent communication skills, and collaboration skills within the team.
Mandatory Skills
- Programming Languages: Proficiency in Python (3.x) and SQL.
- ML Frameworks and Libraries: Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
- Databases: Proficiency in SQL and NoSQL databases.
- Mathematics and Algorithms: In-depth knowledge of mathematics, statistics, and algorithms.
- ML Modules and REST API: Proficient with ML modules and REST API.
- Version Control: Hands-on experience with version control applications (GIT).
- Model Deployment and Monitoring: Experience with model deployment and monitoring.
- Data Processing: Ability to turn unstructured data into useful information (e.g., auto-tagging images, text-to-speech conversions).
- Problem-Solving: Analytically agile with strong problem-solving capabilities.
- Learning Agility: Quick to learn new concepts and eager to explore and build new features.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- Experience: Minimum of 4 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.
Key skills/competency
- Machine Learning Engineer
- MLOps
- Python
- SQL
- Cloud Deployment
- Model Management
- DevOps Collaboration
- CI/CD Pipelines
- REST API
- Problem-Solving
Skills & topics
- Machine Learning Engineer
- MLOps
- Python
- SQL
- Cloud Deployment
- Model Management
- DevOps
- CI/CD
- REST API
- Data Science
- Manager
- Team Lead
- Production Support
- Software Engineering
How to get hired
- Tailor your resume: Highlight MLOps experience, Python, SQL, and cloud deployment skills relevant to EXL.
- Showcase problem-solving: Provide examples of how you've resolved production ML issues.
- Quantify achievements: Use metrics to demonstrate impact in model deployment and performance.
- Prepare for technical questions: Brush up on ML frameworks, algorithms, and CI/CD practices.
- Demonstrate leadership: Be ready to discuss mentorship and collaboration experiences.
Technical preparation
Master Python (3.x) and SQL for ML tasks.,Deepen knowledge of ML frameworks and algorithms.,Practice CI/CD pipelines and Git version control.,Prepare for cloud deployment and monitoring scenarios.
Behavioral questions
Describe a challenging ML deployment you managed.,How do you mentor junior machine learning engineers?,How do you collaborate with DevOps and other teams?,Share an example of driving process improvement.
Frequently asked questions
- What is the typical career progression for a Machine Learning Engineer Manager at EXL?
- At EXL, a Machine Learning Engineer Manager can expect a career path that may lead to Senior Manager or Director roles within the data science or engineering divisions. Progression is often based on demonstrated leadership, successful project delivery, and contributions to innovation in MLOps and AI strategy.
- What are the key technologies used by the Machine Learning team at EXL?
- The EXL Machine Learning team heavily utilizes Python, SQL, various ML frameworks and libraries, and cloud platforms for model deployment and management. They also implement CI/CD pipelines, version control with Git, and work with both SQL and NoSQL databases.
- How important is collaboration with other teams for this Machine Learning Engineer Manager role at EXL?
- Collaboration is crucial. This role requires close work with DevOps engineers, ML scientists, software engineers, data engineers, and front-end developers to ensure seamless integration and optimization of ML models in production environments.
- Does EXL offer remote work options for Machine Learning Engineer Managers?
- Yes, EXL offers a Work From Home (WFH) mode for this position, alongside opportunities to work from their Bangalore, Noida, Pune, Hyderabad, or Gurgaon offices.
- What kind of mentorship is expected from a Machine Learning Engineer Manager at EXL?
- As a Machine Learning Engineer Manager, you will be expected to conduct code reviews and mentor junior team members, fostering a collaborative learning environment and promoting strong interpersonal and communication skills within the team.
- What are the core qualifications for the Machine Learning Engineer Manager position at EXL?
- A Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field, along with a minimum of 4 years of hands-on experience in MLOps, deploying and managing ML models in production, preferably on cloud platforms, are the core qualifications.