AI/ML Engineer

Ambifo; Bengaluru; On-site; INR 2,000,000 - 4,200,000; Full time

Job summary

Ambifo in Bengaluru is seeking an experienced ML engineer to design, train, and deploy ML models and LLM-based applications at scale. You will build end-to-end pipelines, apply MLOps best practices, and collaborate with data engineers on feature stores and data pipelines.

You will stay current with AI research, apply innovations to client projects, and communicate ROI to stakeholders. This role offers opportunities to work on cutting-edge generative AI initiatives in a dynamic team.

Qualifications

• 4+ years hands-on ML engineering or data science experience.
• Strong proficiency in Python, PyTorch or TensorFlow.
• Experience deploying ML models to production (SageMaker, Azure ML, or Vertex AI).
• Familiarity with LLM frameworks and MLOps tools.
• Bachelor’s or Master’s degree in CS, Math, or related field.

Responsibilities

• Design, train, and deploy ML models in production environments.
• Build and optimize LLM-based apps using RAG, fine-tuning, and prompts.
• Develop end-to-end ML pipelines with MLOps best practices.
• Work with large-scale data using Spark/Databricks/AWS EMR.
• Collaborate with data engineers on feature stores and data pipelines.
• Implement model monitoring, A/B testing, and continuous improvement.
• Present AI/ML solutions and ROI to non-technical stakeholders.
• Stay current with AI research and apply innovations to client projects.

Skills

ML engineering

Python

PyTorch

TensorFlow

MLOps

AWS SageMaker

Education

Bachelor's or Master's in CS/Math or related

Tools

LangChain

LlamaIndex

Hugging Face

MLflow

Kubeflow

Spark

Databricks

AWS EMR

Pinecone

Weaviate

ChromaDB

Job description

Python TensorFlow LLMs AWS SageMaker MLOps

About This Role

Join our AI/ML Practice to build cutting-edge machine learning and generative AI solutions. You will work on projects ranging from predictive analytics to LLM-powered applications, deploying models at scale for enterprise clients across industries.

Responsibilities

• Design, train, and deploy machine learning models in production environments
• Build and optimize LLM-based applications using RAG, fine-tuning, and prompt engineering
• Develop end-to-end ML pipelines with MLOps best practices
• Work with large-scale data processing using Spark, Databricks, or AWS EMR
• Collaborate with data engineers to build feature stores and data pipelines
• Implement model monitoring, A/B testing, and continuous improvement processes
• Present AI/ML solutions and ROI to non-technical stakeholders
• Stay current with latest AI research and apply innovations to client projects

Requirements

• 4+ years of hands-on experience in ML engineering or data science
• Strong proficiency in Python, PyTorch or TensorFlow
• Experience deploying ML models to production (AWS SageMaker, Azure ML, or GCP Vertex AI)
• Familiarity with LLM frameworks: LangChain, LlamaIndex, or Hugging Face
• Experience with MLOps tools: MLflow, Kubeflow, or similar
• Strong understanding of statistical modeling and ML algorithms
• Bachelor's or Master's degree in CS, Mathematics, or related field

Nice to Have

• Experience with generative AI and prompt engineering
• Publications or contributions to ML open-source projects
• AWS Machine Learning Specialty certification
• Experience with real-time ML inference at scale
• Knowledge of vector databases (Pinecone, Weaviate, ChromaDB)

Competitive salary with performance bonuses

Annual certification sponsorship

Health insurance for you and your family

24 paid time off days per year

Conference and research paper publication support

GPU compute credits for personal projects