AI Engineer

Bootlabs; Mumbai; Vor Ort; INR 1.500.000 - 3.500.000; Vollzeit

Zusammenfassung

Bootlabs in Mumbai seeks an energetic AI Engineer / Data Scientist with 4 to 6 years of experience to design, build, and scale production-grade ML and Generative AI systems. You will work at the intersection of data science and software engineering, delivering end-to-end solutions on AWS/Azure/GCP.

You will collaborate with cross-functional teams to deploy LLM integrations, RAG pipelines, and robust ML workflows, writing clean Python code and driving model performance in production.

Qualifikationen

• Experience with data science, ML, or AI engineering and shipping production systems.
• Advanced, hands-on Python and core data/ML libraries (Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow).
• Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex), vector databases (Pinecone, Milvus, Chroma), and Hugging Face ecosystems.
• Solid working knowledge of at least one major cloud provider (AWS, Azure, or GCP) for deploying AI workloads.
• Familiarity with Docker/containerization, REST APIs (FastAPI), Git, and CI/CD pipelines.
• Strong understanding of ML lifecycles, metrics, data preprocessing, and production pitfalls like data drift.

Aufgaben

• GenAI & AI Solution Development: Design and deploy modern Generative AI solutions, including LLM integrations, RAG pipelines, prompt engineering, and agentic workflows.
• Production Systems & MLOps: Build, containerize, and deploy scalable ML inference pipelines and APIs; monitor, optimize, and troubleshoot performance and costs in cloud environments.
• Model Development & Experimentation: Apply strong ML fundamentals, perform EDA, feature engineering, fine-tuning, and rigorous model evaluation.
• Cloud Infrastructure (CSP): Leverage cloud services to architect data and AI workflows, using managed services, container registries, and serverless compute.
• Cross-Functional Collaboration: Partner with software eng, product, and data teams to integrate AI into customer-facing apps.

Kenntnisse

Python

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

LangChain

LlamaIndex

Pinecone

Milvus

Chroma

Hugging Face

AWS

Azure

GCP

Docker

FastAPI

Git

CI/CD

ML lifecycle

Ausbildung

Bachelor's or Master's in CS/DS/AI

Tools

LangChain

LlamaIndex

Pinecone

Milvus

Chroma

Hugging Face

Jobbeschreibung

About the Role

We are looking for an energetic, hands-on AI Engineer / Data Scientist with 4 to 6 years of

experience to join our core AI and engineering team. In this role, you will design, build, and

scale production-grade machine learning and Generative AI systems.

You will work at the intersection of data science and software engineering, taking models from

conception and functional development to scalable cloud deployment on AWS/Azure/GCP. If

you are passionate about building high-performance AI solutions, working with LLMs/GenAI

tools, and writing clean, production-ready Python code, we want to hear from you.

Key Responsibilities

GenAI & AI Solution Development: Design and deploy modern Generative AI

solutions, including Large Language Model (LLM) integrations, Retrieval-Augmented

Generation (RAG) pipelines, prompt engineering, and agentic workflows.

Production Systems & MLOps: Build, containerize, and deploy scalable machine

learning inference pipelines and APIs into production environments. Monitor, optimize,

and troubleshoot model performance, latency, and costs in cloud environments.

Model Development & Experimentation: Apply a strong functional understanding of

machine learning and deep learning algorithms. Perform exploratory data analysis,

feature engineering, fine-tuning, and rigorous model evaluation.

Cloud Infrastructure (CSP): Leverage cloud services (AWS, Azure, or GCP) to

architect robust data and AI workflows, utilizing managed AI services, container

registries, and serverless/compute instances.

Cross-Functional Collaboration: Partner closely with software engineering, product,

and data teams to seamlessly integrate AI capabilities into customer-facing applications.Required Qualifications & Skills

Experience: 36 years of professional experience in data science, machine learning, or

AI engineering, with a proven track record of shipping systems to production.

Programming: Advanced, hands-on proficiency in Python and its core data/ML libraries

(e.g., Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow).

Generative AI & Modern AI Tools: Hands-on experience with LLM orchestration

frameworks (e.g., LangChain, LlamaIndex), vector databases (e.g., Pinecone, Milvus,

Chroma), and Hugging Face ecosystems.

Cloud Platforms (CSP): Solid working knowledge of at least one major cloud

provider—AWS, Microsoft Azure, or Google Cloud Platform (GCP)—for deploying

and managing AI workloads.

Production & Software Engineering Mindset: Familiarity with Docker/containerization,

REST API development (FastAPI), Git version control, and CI/CD pipelines.

Core Fundamentals: Strong functional understanding of model development lifecycles,

statistical evaluation metrics, data preprocessing, and overcoming common production

pitfalls (like data drift or latency bottlenecks).

Preferred Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence,

or a related technical field.

Experience fine-tuning open-source LLMs or implementing advanced RAG

optimizations.

Certifications from AWS, Azure, or GCP in Machine Learning or Cloud Architecture.