Machine Learning Engineer

Job Description

Job Summary:

We are seeking a skilled Machine Learning Engineer to design, build, and optimize ML models across various domains including document intelligence, object detection, and retrieval-based language generation. This role requires strong foundational knowledge in machine learning, deep learning, and statistics along with hands-on experience in deploying practical, scalable solutions.

Key Responsibilities:

• Design and implement ML pipelines: preprocessing, training, evaluation, and deployment

• Work with OCR frameworks (DocTR, Tesseract, PaddleOCR) for document processing

• Apply object detection models such as YOLO for visual recognition tasks

• Develop and fine-tune RAG pipelines and integrate with LLMs like GPT, LLaMA, Mistral

• Use VLMs (e.g., CLIP, BLIP, LLaVA, GPT-4V) for multimodal tasks

• Build, tune, and evaluate supervised, unsupervised, and ensemble models using XGBoost, LightGBM, and scikit-learn

• Implement model evaluation techniques such as cross-validation, confusion matrix, ROC-AUC, etc.

• Perform data cleaning, wrangling, and visualization using pandas, NumPy, matplotlib, and seaborn

• Collaborate with DevOps teams for model tracking, CI/CD, and ML Ops processes

Requirements:

• Experienced professional with strong command of machine learning concepts and Python

• Proficient in developing and tuning models for real-world applications

• Comfortable working in a fast-paced, collaborative team environment

Core Technical Skills:

• Languages & Libraries: Python, scikit-learn, XGBoost, LightGBM

• ML Techniques: Supervised, Unsupervised, Ensemble Learning

• OCR Frameworks: DocTR, Tesseract, PaddleOCR

• Object Detection: YOLO, other deep learning models

• LLMs & RAG: GPT, LLaMA, Mistral; Retrieval-Augmented Generation

• VLMs: CLIP, BLIP, LLaVA, GPT-4V

• Evaluation: Cross-validation, ROC-AUC, confusion matrix

• Data Analysis: pandas, NumPy, matplotlib, seaborn

• Frameworks: TensorFlow, PyTorch

• ML Ops: Model versioning, CI/CD, experiment tracking

Nice to Have:

• Familiarity with HuggingFace Transformers

• Experience working with GPU-backed infrastructure for training models

• Exposure to cloud services (AWS, GCP, Azure)

Key Attributes:

• Strong analytical mindset with deep problem-solving skills

• Ability to own end-to-end ML pipelines

• Clear communicator, comfortable working with technical and non-technical stakeholders

What We Offer:

• 5 working days (Monday–Friday)

• Market-competitive salary

• Medical insurance

• Provident fund

• Free pick & drop service

• Project-based exposure in AI-powered systems across multiple domains

Job Skill

Job Details