AI/ML Engineer

Job highlights

• Minimum 3 years of experience in building and deploying production-level ML / DL systems.
• Cloud & MLOps: AWS SageMaker,GCP Vertex AI,Azure ML,MLflow,Kubeflow,Docker,Kubernetes. Data & Compute: Apache Spark,BigQuery,RabbitMQ,S3,EC2. Embedding Stores & Vector Search: FAISS,Pinecone,ChromaDB. Orchestration & APIs: Apache Airflow,Docker Deployment,and FastAPI are a must

We are seeking experienced AI/ML Engineers who will be responsible for developing and driving new business opportunities internationally. The incumbent will be responsible for discovering sales opportunities and creating qualified leads.

Key Responsibilities:

• Develop ML and Deep Learning Solutions: Create predictive, classification, and optimization models using supervised, unsupervised, and reinforcement learning.
• Design and Implement Generative AI Systems: Build and fine-tune Large Language Models (LLMs) and diffusion models for a range of use cases involving text, code, and multi-modal data.
• Build Scalable Recommendation Engines: Develop and optimize recommendation systems using collaborative filtering, content-based filtering, hybrid models, or sequential models.
• Cloud-Native ML Engineering: Deploy and manage machine learning pipelines and APIs in cloud environments (AWS, GCP, Azure),ensuring scalability, observability, and cost efficiency.
• End-to-End ML Lifecycle Ownership: Own the model lifecycle from feature engineering and experimentation to deployment, CI/CD, monitoring, and iteration.
• Collaborate Across Functions: Work with cross-functional teams including product managers, engineers, and data scientists to translate business goals into AI-powered solutions.

Core Requirements

• Minimum 3 years of experience in building and deploying production-level ML/DL systems
• Develop proofs of concept AI/ML-based solutions and services and demonstrate them to Business stakeholders
• Design and deliver ML architecture patterns operable in native and hybrid cloud architectures.
• Create Functional and technical specifications for AI/ML solutions.
• Implement machine learning algorithms in services and pipelines that can be used on a web scale.
• Design, develop, and implement Generative AI models using state-of-the-art techniques.
• Collaborate with cross-functional teams to define project goals, research requirements, and develop innovative solutions.
• Strong understanding of transformer architectures and deep learning model design
• Hands-on experience in building at least one production-grade Deep learning solution or Generative AI solution
• Expertise in Python programming with a focus on:
  Code optimization and profiling
  Multi-threading and multiprocessing
  Object-oriented programming and design principles
• Experience deploying models in a cloud-native environment with strong MLOps practices
• Understanding of model evaluation, observability, A/B testing, and feedback loops
• Excellent problem-solving and analytical skills.
• Strong communication and presentation skills.

Technical Stack

• Languages: Excellent understanding of object-oriented concepts and Python.
• ML/DL Frameworks:
  Machine Learning: Scikit-learn, XGBoost, LightGBM
  Deep Learning: PyTorch, TensorFlow, Keras
  GenAI: Hugging Face Transformers, LangChain, OpenAI APIs, Gemini, Agentic Framework
• Cloud & MLOps: AWS SageMaker, GCP Vertex AI, Azure ML, MLflow, Kubeflow, Docker, Kubernetes
• Data & Compute: Apache Spark, BigQuery, RabbitMQ, S3, EC2
• Embedding Stores & Vector Search: FAISS, Pinecone, ChromaDB
• Orchestration & APIs: Apache Airflow, Docker Deployment, and FastAPI are a must

Preferred Qualifications

• Experience with multi-modal models combining text, vision, or audio
• Familiarity with Retrieval-Augmented Generation (RAG), embedding stores, and agent-based orchestration (LangGraph, ReAct)
• Open-source contributions in AI/ML or GenAI ecosystems
• Certifications in cloud-based machine learning platforms (AWS/GCP/Azure)

Education

• B.Tech / M.Tech / Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field
• Equivalent practical experience in developing scalable AI solutions will also be considered

What Company Offers:
Excellent career growth opportunities and exposure to multiple technologies.
Fixed weekday day schedule, meaning, you ll have your weekends off!
Family Medical Insurance.
Unique leave benefits and encashment options based on performance.
Long term growth opportunities.
Fun family environment surrounded by experienced developers.
Various internal employee rewards programs based on Performance.
Opportunities for various other Bonus programs - for training hours taken,
certifications, special value to business through idea and innovation.
Work life Balance - flexible work timings, early out Fridays, various social and cultural activities etc.
Company Sponsored International Tours