McLaren Strategic Solutions - Machine Learning Engineer - Generative AI & NLP (3-5 yrs)

Experience Level : 3+ years

Location : India, Remote

Role Overview :

McLaren Strategic Solutions is seeking a skilled Machine Learning Engineer with strong experience in developing AI solutions leveraging Large Language Models (LLMs) and NLP techniques.

This role involves designing and implementing AI applications, including predictive analytics, conversational AI, and decision automation, using existing LLMs and NLP capabilities.

Any prior experience with advanced GenAI techniques like RetrievalAugmented Generation (RAG), Agentic AI, and exposure to computer vision is a plus.

Responsibilities :

- Develop, deploy, and optimize AI solutions that leverage existing Large Language Models (LLMs) such as GPT, BERT, and other transformer-based models for NLP tasks.

- Apply LLMs to real-world applications, including legal predictive analytics, conversational AI, robotic accounting, forecasting, and anomaly detection, with a focus on NLP and language understanding.

- Build and fine-tune NLP models for tasks such as text generation, summarization, document understanding, and dialogue systems.

- Apply advanced GenAI techniques, such as Retrieval-Augmented Generation (RAG) for enhanced context-aware responses, and Agentic AI for complex decisionmaking capabilities in specific use cases, as appropriate.

- Conduct data preparation, wrangling, and feature engineering to support effective NLP model training and deployment.

- Collaborate with cross-functional teams to demonstrate the application of NLP and LLM capabilities in solving customer challenges.

- Design and optimize model training and deployment pipelines for scalability and efficiency in production environments.

- Leverage cloud-based ML tools (e.g, AWS SageMaker, Azure ML Studio) to streamline deployment of NLP and GenAI models.

- Follow agile methodologies and software lifecycle best practices using tools such as JIRA, Confluence, and Git.

Qualifications :

- Bachelor's or master's degree in computer science, Engineering, Mathematics, or a related field, specializing in Machine Learning or AI.

- Strong understanding of Large Language Models and NLP, with experience in applying these models to solve real-world problems.

- Extensive hands-on expertise in Python and commonly used ML libraries/tools, such as NumPy, SciPy, pandas, scikit-learn, and visualization tools like matplotlib.

- Proficiency in deep learning frameworks (TensorFlow, Keras, PyTorch) and transformer libraries (e.g, Hugging Face, spaCy, NLTK).

- Experience in using LLMs and NLP techniques for applications such as text generation, summarization, language understanding, and conversational AI.

- Familiarity with MLOps practices and tools for managing, monitoring, and deploying large-scale NLP models.

- Experience with cloud platforms (AWS, Azure) for deploying and optimizing machine learning solutions.

- Knowledge of Software Development Life Cycle (SDLC) and agile processes, including Test-Driven Development (TDD).

- Bonus : Exposure to advanced GenAI solutions and computer vision, including :

1. Retrieval-Augmented Generation (RAG) : Techniques for enhancing responses using external databases or document sources for context-aware language generation.

2. Agentic AI : Experience with AI models capable of autonomous decisionmaking or multi-step reasoning in complex applications.

3. Computer Vision : Basic exposure to computer vision libraries and techniques, with understanding of tasks like object detection, image classification, or facial recognition