Machine Learning Engineer

The job overview for the Machine Learning Engineer role at InMobi is to work in a highly fertile environment for building, experimenting, refining, and affecting real change from computational advertising models. The role requires a strong background in hands-on coding for training and deployment of ML/AI models, as well as dealing with large-scale data. The ideal candidate should have a good understanding of modern DL techniques and proficiency in programming languages such as Python, Java, or C++.

Design, develop, and deploy machine learning models and algorithms

Create, store, and retrieve embeddings in the most efficient manner

Train and deploy Deep Learning models

Run inference at scale

Collaborate with data science and engineering teams to build models using AI tools

Deal with large scale data

Have a strong background in hands-on coding for training and deployment of ML/AI models

Be well-versed with Deep Learning and modern DL techniques

Possess strong programming skills in languages such as Python, Java, or C++

• Education: Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field. A Master's or Ph.D. in a relevant discipline is preferred.
• Experience: 6+ years of experience working as a Machine Learning Engineer or in a similar role. Demonstrated experience in designing, developing, and deploying machine learning models and algorithms.
• Strong programming skills: Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is required. Familiarity with Microsoft Azure is a plus.
• Solid understanding of machine learning techniques: Strong theoretical and practical knowledge of machine learning algorithms, including supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing.
• Data handling and preprocessing: Experience with data wrangling, cleaning, and preprocessing techniques. Proficiency in PySpark and working with large datasets is desirable.
• Software engineering skills: Familiarity with software development practices and version control systems (e.g., Git). Ability to write clean, modular, and maintainable code.
• Problem-solving mindset: Strong analytical and problem-solving skills to tackle complex data-driven challenges. Ability to break down complex problems into manageable tasks and propose effective solutions.

• Design, develop, and implement machine learning models and algorithms
• Work closely with data scientists, data engineers, and domain experts
• Perform exploratory data analysis to gain insights and identify patterns or trends
• Transform raw data into meaningful features
• Develop and implement training pipelines
• Evaluate model performance and fine-tune models
• Collaborate with software engineers to deploy machine learning models
• Stay up to date with the latest advancements in machine learning
• Collaborate effectively with cross-functional teams
• Understand requirements, define project goals, and deliver high-quality machine learning solutions