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Urgent! AI Solutions Engineer Job Opening In Industrial Area – Now Hiring TecOrb Technologies - We Believe in Challenges

AI Solutions Engineer



Job description

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

Position:AI/ML Engineer (Mid-Level)

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.


- 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.


Required Skill Profession

Computer Occupations



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