AI/ML Engineer

TecOrb Technologies - We Believe in Challenges; Dadri; On-site; INR 600,000 - 1,000,000; Full time

Benefits offered by this job

Competitive compensation

Performance-based incentives

Collaborative startup culture

Job summary

A technology solutions company in Dadri is seeking an AI/ML Engineer with a strong background in NLP and deep learning. You will design and deploy cutting-edge AI solutions, work collaboratively with various teams, and contribute to innovative projects. Strong expertise in Python, ML frameworks, and vector databases is essential. This role offers competitive compensation and opportunities for growth in a dynamic environment.

Qualifications

• Strong hands-on background in NLP, deep learning, and reinforcement learning.
• Experience with creating and deploying machine learning models.
• Strong debugging and analytical skills.

Responsibilities

• Design, train, and fine-tune ML/DL models.
• Implement RAG pipelines using vector databases.
• Collaborate with backend engineers to expose models as APIs.

Skills

Python

NLP

Vector databases

MLOps tools

Cloud platforms

Linear algebra

Debugging

Agile methodologies

Education

Mtech or PhD in relevant field

Tools

PyTorch

TensorFlow

Docker

Kubernetes

MLflow

Job description

AI/ML Engineer (Mtech or PhD) – LLMs, RAG, Reinforcement Learning

Experience: Does not required | Location: Noida, UP

Employment Type: Full-time

Studies: Mtech or PhD

About the Role

We are building enterprise-grade AI/ML solutions including SLMs, LLMs, RAG‑based knowledge systems, reinforcement learning, and agentic AI. As a Mid‑level AI/ML Engineer, you will design, train, and deploy machine learning models, collaborate with our product and engineering teams, and ensure scalable integration of AI models into real‑world applications. This role is ideal for someone with a strong hands‑on background in NLP, deep learning, and reinforcement learning, who is eager to grow by working on cutting‑edge AI projects at scale.

Key Responsibilities

• Design, train, and fine‑tune ML/DL models (with focus on transformers, SLMs, LLMs, and recommender systems).
• Implement RAG pipelines using vector databases (Pinecone, Weaviate, FAISS) and frameworks like LangChain or LlamaIndex.
• Contribute to LLM fine‑tuning using LoRA, QLoRA, and PEFT techniques.
• Work on reinforcement learning (RL/RLHF) for optimizing LLM responses.
• Build data preprocessing pipelines for structured and unstructured datasets.
• Collaborate with backend engineers to expose models as APIs using FastAPI/Flask.
• Monitor and optimize model performance (latency, accuracy, hallucination rates).
• Use MLflow / Weights & Biases for experiment tracking and versioning.
• Stay updated with the latest research papers and open‑source tools in AI/ML.
• Contribute to code reviews, technical documentation, and best practices.

Required Skills & Qualifications

• Strong in Python (NumPy, Pandas, Scikit‑learn, PyTorch, TensorFlow).
• Solid understanding of NLP and LLM architectures (Transformers, BERT, GPT, LLaMA, Mistral).
• Practical experience with vector databases (Pinecone, FAISS, PgVector).
• Basic knowledge of MLOps tools – Docker, Kubernetes, MLflow, CI/CD.
• Basic knowledge of cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure ML).
• Good grasp of linear algebra, probability, statistics, optimization.
• Strong debugging, problem‑solving, and analytical skills.
• Familiarity with Agile methodologies (Scrum, Jira, Git).

Nice‑to‑Have Skills

• Experience with RLHF pipelines.
• Open‑source contributions in AI/ML.

Soft Skills

• Strong communication – able to explain AI concepts to technical & non‑technical stakeholders.
• Collaborative – works well with product, design, and engineering teams.
• Growth mindset – eager to learn new AI techniques and experiment.
• Accountability – able to deliver end‑to‑end model pipelines with minimal supervision.
• Can work in a team.

What We Offer

• Work on cutting‑edge AI projects with real‑world enterprise impact.
• Exposure to LLMs, reinforcement learning, and agentic AI.
• Collaborative startup & service culture with room for fast growth.
• Competitive compensation + performance‑based incentives.

Seniority level

Entry level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting