AI/ML ENGINEER

Job Description & Skill Requirement:

We’re seeking a highly skilled AI/ML Engineer to join our engineering team in USA. his role requires a strong foundation in computer science, statistics, and data science, along with hands-on experience in modern ML frameworks.

Required Experience and Exposure

• Bachelor’s or master’s degree in computer science, Machine Learning, Business Analytics, Data Science or related field
• Proven experience in building and deploying ML models in real-world applications
• Strong programming skills in Python (preferred), Gherkin.
• Solid understanding of machine learning algorithms, deep learning, and statistical modeling
• Experience with any of the cloud platforms (AWS or any) and ML tools (Databricks, MLflow, etc.)

Job Duties and Responsibilities:

• Develop AI-driven solutions and intelligent agents tailored to automotive applications, leveraging Python, Gherkin, C++, and modern AI/ML frameworks across both front-end and back-end systems.
• Build and implement AI-powered tools to streamline and enhance various stages of automotive testing and validation.
• Integrate and manage large language models (LLMs) such as Llamas, ChatGPT, and Gemini using AWS Bedrock and Amazon SageMaker for inference, deployment, and fine-tuning.
• Fine-tune LLMs and AI models to optimize performance and accuracy for domain-specific automotive use cases.
• Deploy, monitor, and maintain AI systems in production environments, ensuring reliability, scalability, and compliance.
• Collaborate closely with cross-functional teams—including data scientists, HIL testers, and feature owners—to embed AI capabilities into automotive system architectures.

Required Skills:

• Programming: Python, Exposure to C++

• Behavior Driven Development: Gherkin

• Cloud Platforms: AWS

• Cloud Services: AWS Bedrock and Amazon SageMaker

Preferred Skills:

• ML Frameworks: (Example: TensorFlow, PyTorch, Scikit-learn)

• Data Management and Analysis: (Example: SQL, Spark, Pandas)

• Devops/ Deployment: exposure to Docker or Kubernetes, CI/CD pipeline etc