Machine Learning Engineer

As a Machine Learning Engineer at InMobi, you will be instrumental in designing, developing, deploying, and maintaining cutting-edge ML systems that power our product experiences. We're looking for someone with a passion for elegant problem-solving, rapid experimentation, and owning end-to-end machine learning workflows. You will work closely with data scientists and cross-functional teams to build robust data pipelines, scalable platforms, and production-ready ML services.

Responsibilities:

• Model Development and Deployment: Design, train, and deploy machine learning models with a strong focus on fast, reliable experimentation. Build APIs and microservices to serve ML models at scale.
• Feature Development and Engineering: Design and deliver backend features and efficiently deliver features. Work closely with the analytics, architects and PM to deliver feature requests as per ETA.
• Identify solutions that can help us improve scalability, minimise bugs and reduce cost. Understanding of when to escalate questions/issues that arise during development. Able to efficiently diagnose bugs and issues. Familiar with various design and architectural patterns
• Pipeline and Infrastructure: Develop and maintain data ingestion, preprocessing, and model training pipelines. Deploy scalable data and model solutions that improve efficiency across ML workflows.
• Collaboration and Integration: Work closely with. Define and execute end-to-end ML solutions from ideation to production.
• Monitoring and Research: Monitor model performance in production, using statistical methods to ensure robustness.
• Ownership and Delivery: Lead or contribute to POCs and full-scale ML feature rollouts.
• Manage project deadlines and deliverables in an agile environment.

Requirements:

• Bachelor's degree with 4+ years OR Master's degree with 3+ years in Computer Science, Machine Learning, Data Science, or related field.
• Proven experience in developing and deploying ML models in production.
• Strong proficiency in Python and ML libraries like TensorFlow, PyTorch, or scikit-learn, Spark, Java, and distributed systems.
• Understanding of statistical methods and hypothesis testing.
• Comfortable working with structured and unstructured data.
• Experience working in collaborative, cross-functional teams.
• Loves to code and learn new concepts, technologies and frameworks

Preferred Qualifications:

• Demonstrated ability to rapidly validate hypotheses through experimentation.
• Experience in building recommendation systems or similar ML applications.
• Exposure to advertising, ranking, or personalisation systems is a significant plus.
• Familiarity with SQL, data warehousing, and distributed data systems.
• Prior research experience or involvement in a data science-focused role.
• Strong mathematical foundation, particularly in statistics and linear algebra.
• Excellent verbal and written communication skills.
• Hands-on experience in Databricks is a plus.
• Experience in the ad tech industry is a plus.

Good to Have:

• Experience: 2-5 years of development experience.
• Education: B. E. / B. Tech in Computer Science or equivalent.
• Strong development and coding experience in one or more programming languages like OO Programming (Java), Scala, Spark, Python. Expertise in Data Structures, Algorithms, Concurrency.
• Experience working on Big Data technologies and applications.
• Experience in microservices architecture, multi-threading, performance-oriented programming and design skills.
• Good organisation, communication and interpersonal skills.
• Must be a proven performer and team player who enjoys challenging assignments in a high-energy, fast-growing, and start-up workplace
• Must be a self-starter who can work well with minimal guidance and in a fluid environment.
• Provide good attention to detail.
• Must be excited by challenges surrounding the development of a highly scalable and distributed system for building audience targeting capabilities
• Agility and ability to adapt quickly to changing requirements, scope and priorities.

Nice to have skills:

• Experience in the online advertising domain.
• Experience working on massively large-scale data systems in production environments.
• Experience in leveraging user data for behavioural targeting and ad relevance.
• Experience in the Big Data analytics domain.
• Experience building products that are powered by data and insights.
• Experience hosting and deploying applications on public clouds like Microsoft Azure, GCP, and AWS.