ML Engineer II

Nissan is a pioneer in Innovation and Technology. With a focus on Mobility, Operational Excellence, Value to our Customers and Electrification of vehicles, you can expect to be part of a very exciting journey here at Nissan.
Nissan is going after a massive Digital Transformation backed by leading technologies across the organization globally. We are committed to building a diverse, entrepreneurial organization, and our current team is a strong evidence of that. Our people are what drive the business forward. At Nissan Digital, you will be part of a dynamic team with ample opportunities to grow and make a difference. Responsibilities:
Assist in developing, training, and optimizing machine learning models for various applications. Work with large datasets, performing data preprocessing, feature engineering, and model evaluation. Collaborate with data scientists and software engineers to integrate ML models into production environments. Conduct experiments to improve model accuracy and efficiency. Write clean, efficient, and well-documented code for ML model development. Stay updated with the latest advancements in ML algorithms and technologies. Key Competencies:
Strong analytical and problem-solving skills. Ability to understand and implement ML algorithms effectively. Good communication skills to collaborate with cross-functional teams. Attention to detail and a structured approach to work. GenAI: Curiosity and experimentation with LLMs & GenAI tools (e.g., ChatGPT, Gemini) and prompt tuning MLOps: Learning foundations of model deployment, version control, and experiment tracking Relevant Work Exp : 2-5 years Technical Skills:
Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn. Experience with data manipulation using Pandas and NumPy. Familiarity with cloud platforms like AWS, Azure, or GCP for ML model deployment. Knowledge of SQL and database management. Understanding of software development best practices (Git, Docker, CI/CD). Behavioral Competencies:
Adaptability: Open to learning and applying new ML techniques, tools, and frameworks. Learning Agility: Willingness to experiment, analyze failures, and continuously improve skills. Teamwork: Works collaboratively with peers, takes feedback constructively, and contributes to team success. Certifications (Optional):
TensorFlow Developer Certification AWS Certified Machine Learning - Specialty Microsoft Certified: Azure AI Engineer Associate Google Professional Machine Learning Engineer Trivandrum Kerala India