AI/ML Engineer

Turbostart; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Turbostart is seeking an AI/ML Engineer to develop intelligent systems for real product decisions. You will design and maintain machine learning models, contributing to generative AI capabilities and collaborating with cross-functional teams.

The ideal candidate will have 4-6 years of experience and strong Python skills, as well as familiarity with ML frameworks like PyTorch and TensorFlow. This role demands a hands-on approach, encompassing the full ML lifecycle from research to production.

Qualifications

• 4+ years of hands-on experience in machine learning or applied AI roles.
• Experience building prediction and/or forecasting models in a production environment.
• Strong Python skills and familiarity with ML frameworks.

Responsibilities

• Design, build, and maintain machine learning models for prediction and forecasting.
• Work on Generative AI features including LLM integration and prompt engineering.
• Collaborate with product teams to turn ambiguous problems into working models.

Skills

Machine Learning

Generative AI

Python

Data Exploration

Feature Engineering

Tools

PyTorch

TensorFlow

Scikit-learn

AWS

GCP

Azure

Job description

What we are looking for:

We are looking for an AI/ML Engineer to help us build intelligent systems that power real product decisions. You’ll work on predictive and forecasting models, contribute to our Generative AI capabilities, and collaborate closely with a lean agile team that ships fast and stays close to users. This is a hands‑on role; you’ll go from research and experimentation to production with minimal overhead.

Experience Required

4‑6 years

What You’ll do

• Design, build, and maintain machine learning models for prediction and forecasting use cases.
• Work on Generative AI features — including LLM integration, prompt engineering, fine‑tuning, and RAG pipelines.
• Collaborate with product and engineering teams to turn ambiguous problems into working models in production.
• Evaluate model performance, monitor for drift, and iterate based on real‑world feedback.
• Contribute to the full ML lifecycle: data exploration, feature engineering, training, evaluation, and deployment.
• Stay current with the fast‑moving AI/ML landscape and bring relevant ideas to the team.

Responsibilities

• 4+ years of hands‑on experience in machine learning or applied AI roles.
• Proven experience building prediction and/or forecasting models in a production environment.
• Experience working with Generative AI — LLMs, prompt engineering, fine‑tuning, embeddings, or RAG.
• Strong Python skills; familiarity with ML frameworks such as PyTorch, TensorFlow, or scikit‑learn.
• Comfortable working with structured and unstructured data, including feature engineering and preprocessing pipelines.
• Experience deploying and monitoring models in cloud environments (AWS, GCP, or Azure).
• Ability to communicate findings and trade‑offs clearly to both technical and non‑technical stakeholders.

Nice to have

• Experience with time‑series forecasting libraries (eg, Prophet, NeuralProphet, Darts).
• Familiarity with vector databases (e.g, Pinecone, Weaviate, pgvector) for semantic search or RAG.
• Knowledge of MLOps practices and tooling (e.g., MLflow, Weights & Biases, Airflow).
• Prior work in a startup or fast‑paced product environment.

Who you are:

• Pragmatic — you know when a simple model beats a complex one, and you ship accordingly.
• Curious and self‑directed — you follow the latest AI research and know how to apply it practically.
• Ownership mentality — you take models all the way to production and care about their real‑world impact.
• Collaborative — you work well across engineering, product, and design without needing hand‑holding.