Senior Machine Learning Engineer

Job Description Senior ML Engineer

Role Name : Senior Machine Learning Engineer

Experience : 3-6 years

Department : Data Science

Role :

As a Senior ML Engineer and Team Lead, you will be the driving technical and operational force behind our vision-based analytics pipelines. You will operate as a "player-coach", balancing hands-on model development and edge deployment with the management of a small team of ML engineers. You will design state-of-the-art computer vision modelsranging from classic image processing to modern transformer architecturesand ensure they run efficiently on edge devices (NVIDIA Jetson) using modern MLOps and CI/CD practices.

Key Responsibilities :

- Team Leadership & Management : Manage and mentor a small team of ML engineers. Guide their technical development, oversee task delegation, conduct 1-on-1s, and foster a culture of engineering excellence and collaboration.

- Technical Roadmapping : Work closely with product and engineering leadership to define ML project scopes, timelines, and technical architecture.

- Model Development : Design, train, and evaluate Computer Vision models for object detection, image classification, segmentation, and Optical Character Recognition (OCR).

- Algorithm Selection : Apply the right tool for the job, balancing classic CV algorithms, standard Deep Learning approaches (CNNs, YOLO, etc.), and state-of-the-art Vision Transformers (ViT, DETR).

- Edge Optimization & Deployment : Optimize models for real-time inference on edge devices (NVIDIA Jetson) using frameworks like TensorRT, ONNX, or DeepStream.

- MLOps & Infrastructure : Architect and maintain end-to-end MLOps pipelines. Containerize applications using Docker and automate workflows using CI/CD pipelines.

- Production Monitoring : Implement telemetry and monitoring solutions to track model drift, hardware health, and inference performance on distributed edge devices in the field.

- Code Quality : Write clean, production-ready, and highly optimized Python code, and enforce these standards across your team through code reviews.

Required Qualifications :

- Experience : 3+ years of industry experience in Machine Learning, with a heavy focus on Computer Vision in production environments.

- Leadership : 1+ years of experience leading, managing, or formally mentoring an engineering or data science team.

- Programming : Strong proficiency in Python and its scientific computing ecosystem (NumPy, SciPy, Pandas).

- Computer Vision Expertise :

1. Solid grasp of classic CV techniques (OpenCV).

2. Deep understanding of DL architectures for detection and classification (PyTorch or TensorFlow).

3. Hands-on experience with OCR systems (e.g., Tesseract, EasyOCR, PaddleOCR).

4. Working knowledge of Transformer-based vision models.

- Edge Deployment : Proven track record of deploying models to edge hardware, specifically NVIDIA Jetson architecture. Experience with model quantization, pruning, and optimization (TensorRT, ONNX Runtime).

- MLOps & DevOps : Hands-on experience with Docker and building automated CI/CD pipelines (GitHub Actions, GitLab CI, or similar).

- Monitoring : Experience setting up monitoring, logging, and remote management for edge deployments.

Preferred (Nice-to-Have) Skills :

- Proficiency in C++ for high-performance edge inference.

- Experience with NVIDIA DeepStream SDK.

- Agile/Scrum project management experience.

- Familiarity with cloud platforms (AWS, GCP, or Azure) and IoT device management.

- Experience with ML lifecycle tools like MLflow, Weights & Biases, or Kubeflow.

Skills

Machine Learning, Computer Vision, Python, PyTorch, Docker, MLOps, Optical Character Recognition