Job Description Machine Learning Engineer We seek a motivated and enthusiastic Machine Learning Engineer to join our team. As a fresher, you will work closely with senior engineers and data scientists to learn, grow, and contribute to various machine learning projects. You will help in building, training, and optimizing machine learning models and work with data to derive meaningful insights. This role is perfect for someone looking to start a career in machine learning, with opportunities for continuous learning and growth. Key Responsibilities: Assist in developing machine learning models : Collaborate with senior engineers to design and build machine learning models for real-world applications. Data preprocessing : Work on cleaning, transforming, and organizing datasets to prepare them for model training. Model evaluation : Help evaluate models using different metrics and assist in tuning hyperparameters to optimize performance. Research and learning : Stay updated on the latest machine learning techniques and best practices through independent learning and team mentorship. Collaborate with teams : Work closely with data scientists, data engineers, and product teams to understand project requirements and assist in solution development. Documentation : Contribute to project documentation, including code comments, model descriptions, and reports. Support model deployment : Assist in integrating models into production systems and monitor their performance over time. Debugging and troubleshooting : Help identify and resolve issues in data processing pipelines and model performance. Qualifications: Education : Bachelor’s /Master’s degree in Computer Science, Machine learning, Data Science, Mathematics, Statistics, or a related field (or equivalent experience). Skills : Basic understanding of machine learning algorithms (e.g., linear regression, decision trees, k-means clustering). Familiarity with programming languages such as Python or R. Knowledge of machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn. Experience with data manipulation tools like Pandas and NumPy. Good problem-solving and analytical skills. Strong desire to learn and grow in the machine learning field. Effective communication and teamwork skills. Preferred Qualifications: Internship or coursework in machine learning, artificial intelligence, or data science. Experience with projects involving machine learning (academic or personal). Familiarity with cloud platforms like AWS, Google Cloud, or Azure is a plus. Exposure to tools like Jupyter Notebooks, Git, and version control systems. Benefits: Competitive entry-level salary. Learning and development opportunities, including mentorship from senior engineers. Flexible work environment with opportunities for remote work. Access to industry-leading tools and technologies.
AI/ML Engineer (Mtech or PhD) – LLMs, RAG, Reinforcement Learning Position : AI/ML Engineer (Mid-Level) Experience : 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. To Apply: Please send your resume and cover letter to 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.