AI/ML Engineer

Creuto Cloud; Khordha; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Creuto Cloud is seeking an AI/ML Engineer with 2–5 years of hands-on experience to design, train, evaluate, and deploy ML models and AI features within our products.

You will collaborate with product managers, backend engineers, and data teams to identify user value, build robust training pipelines, integrate LLMs from providers, and optimize latency and cost in production.

Qualifications

• 2–5 years hands-on experience building and shipping ML models or AI features in production environments.
• Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience with LLMs in production and prompt engineering, context management, and output reliability.
• Comfortable with end-to-end ML lifecycle from data prep to deployment and monitoring.
• Ability to evaluate model quality rigorously and translate user problems into ML tasks.

Responsibilities

• Design, train, evaluate, and deploy machine learning models and LLM-powered features into production systems.
• Build data pipelines for collection, preprocessing, feature engineering, and model training in Python.
• Integrate large language models from OpenAI, Anthropic, and Google into product workflows via prompt tuning.
• Build retrieval augmented generation systems using vector databases like Pinecone or Weaviate.
• Develop evaluation frameworks to measure model quality, accuracy, and performance over time.
• Optimize models for latency and cost in production (quantisation, distillation, batching).
• Monitor AI features in production for quality degradation and unexpected behavior.
• Collaborate with product and engineering to translate user problems into ML tasks and deliverables.
• Stay current on AI research and tooling; bring advances into the team.
• Document models, data pipelines, and evaluation results for technical and non-technical stakeholders.

Skills

Python

ML frameworks

LLMs in production

Prompt engineering

ML lifecycle

Data preprocessing

Clear communication

Tools

MLflow

Weights & Biases

Kubeflow

Pinecone

Weaviate

pgvector

Job description

Job Summary

We are looking for an AI/ML Engineer with 2 to 5 years of experience to build, train, evaluate, and deploy machine learning models and AI-powered features directly into our products. You will work closely with product managers, backend engineers, and data teams to identify where AI creates the most user value, then build and ship those capabilities at production quality. This is a role for engineers who are as comfortable writing a training loop as they are debugging a production inference endpoint.

In This Role, You Will

• Design, train, evaluate, and deploy machine learning models and LLM-powered features into production systems.
• Build pipelines for data collection, preprocessing, feature engineering, and model training using Python and relevant ML frameworks.
• Integrate large language models from providers such as OpenAI, Anthropic, and Google into product workflows using prompt engineering and fine-tuning.
• Build retrieval augmented generation (RAG) systems using vector databases such as Pinecone, Weaviate, or pgvector.
• Develop evaluation frameworks and benchmarks to measure model quality, accuracy, and performance over time.
• Optimise models for latency and cost in production including quantisation, distillation, and batching strategies.
• Monitor AI features in production for quality degradation, hallucination rates, and unexpected behaviours.
• Collaborate with product and engineering to translate user problems into well-defined ML tasks and deliverables.
• Stay current on the latest AI research, models, and tooling and bring relevant advances into the team work.
• Document models, data pipelines, and evaluation results clearly for both technical and non-technical stakeholders.

You Might Thrive in This Role If You

• Have 2 to 5 years of hands-on experience building and shipping ML models or AI features in production environments.
• Are proficient in Python and experienced with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Have worked with LLMs in production and understand the nuances of prompt engineering, context management, and output reliability.
• Are comfortable with the full ML lifecycle from data preparation and training through to deployment and monitoring.
• Can evaluate model quality rigorously and are not satisfied with models that work well on benchmarks but fail in real use.
• Think about user impact first and use technical sophistication in service of solving real problems.
• Communicate clearly about model limitations, tradeoffs, and uncertainties to non-technical collaborators.

Bonus If You Have

• Experience fine-tuning open source models such as LLaMA, Mistral, or Phi using LoRA or similar techniques.
• Familiarity with MLOps tooling including MLflow, Weights and Biases, or Kubeflow.
• Knowledge of multi-modal AI including vision-language models and image generation.
• Experience building agentic AI systems with tool use, memory, and multi-step reasoning.
• Contributions to AI research, open-source ML projects, or published papers.
• Understanding of responsible AI principles including bias detection, fairness, and model safety.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.