Machine Learning Engineer

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

Position

Experience

Location

Employment Type

Studies

About the Role:

AI/ML solutions

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.

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.

• Ensure scalable deployment using Docker, Kubernetes, AWS/GCP/Azure ML services.

• 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, or FAISS or PgVector).

• Basic Knowledge with 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 works 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.

To Apply:

hr@tecorb.com

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, or any other characteristic.