Job Description

We are looking for a motivated and skilled engineer in AI/ML and Generative AI to contribute to the design and development of innovative Analytics solutions. You will work as part of a collaborative, cross-functional team to build scalable models and systems that enhance decision-making, improve operational efficiency, and unlock insights from complex data.

Qualifications

:


Exceptional candidates with a Bachelor's degree in Engineering, preferably in IT, computer science, statistics, or data science, may also be considered. A degree in a relevant field such as Probability, Statistics, Machine Learning, Data Mining, Artificial Intelligence, or Computer Science or engineering disciplines.

Experience

:


Overall experience needed: Must have minimum

3-4

years

of professional experience in the relevant fields and roles such as Data Scientist/AI Engineer/Generative AI engineer or equivalent.

AI/ML:

Development of Data Science/AI and Machine learning based solutions/prototypes/ PoCs for different domains, Solution Architecture Designing, Data Engineering, Algorithm Design, MLOPS

Generative AI

(~1 year required)

and Natural Language processing

- Previous experience working with generative AI and developing solutions covering but not limited to LLMs, LLMOps, Retrieval Augmented Generation, prompt engineering, Understanding of chatbot development and deployment. Understanding of agentic framework.

Technology

:

Must

: Python (Numpy, Pandas), deep learning, NLTK, HuggingFace, TensorFlow, Scikit-Learn, PyTorch, Langchain, Transformers, OpenAI GPT models, Mistral, LLAMA models and any other foundational models


Cloud-Azure/AWS-basic understanding of setting up, deploying, working with & managing cloud VMs

Desired skills and technology

: Databricks, Streamlit, REST API, Flask. Frontend / UI technology experience is a plus.

Other skills:

Skills and mindset:

The candidate should have strong mathematical, analytical, and problem-solving skills, as well as a research-oriented and proactive attitude. The candidate should take ownership and result oriented.

Team skills and collaborative -

Collaborates closely with stakeholders and is a strong team player

Research and innovation:

The candidate should keep up with the latest developments in the relevant fields and seek new ways to leverage technology for better solutions.

Software engineering:

The candidate should be able to understand the requirements, test the solutions, and integrate analytical algorithms into a product.

Good to Have:

Domain experience/exposure: Automotive Domain Experience, Automotive Test Suite Experience, railways, aerospace, automation equipment, Embedded development, software development and testing, engineering and manufacturing, product engineering, design and development.

Responsibilities

:


Use data mining and machine learning techniques to build advanced systems. Design, develop, and validate data science models. Visualize data and explain outcomes. Create data preparation processes and tools. Ensure data ingestion and governance criteria are met. Design, develop, and implement solutions with a focus on Generative AI. Integrate generative AI into existing applications. Fine-tune language models for better performance. Collect, assess, and document requirements. Perform root cause analysis and offer improved approaches. Integrate analytical algorithms into a bigger solution/product. Understand business challenges and formulate data analysis approach. Define data requirements for analysis. Research innovative technologies. Interpret, document, and present analytical results. Build intelligent systems to enrich the end-user experience. * Work with business and solution teams to conceptualize and manage data-driven projects.