Senior ML Engineer Big Entities
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Monthly Salary:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Our client Big Entities is looking for Senior ML Engineer to work remotely.
Location: DHA Phase 3 (Remote)
Timings: 10 AM - 7 PM (Fri - Sat Off days)
Role Summary
We are looking for a hands-on Computer Vision and ML Engineer with deep expertise in deep object detection and strong production delivery skills. You will own end-to-end detection systems from dataset and training pipelines to optimized inference services monitoring and continuous improvement.
Key Responsibilities
- Design train debug and improve state-of-the-art object detection models for real-world conditions
- Build robust training pipelines: datasets augmentation caching versioning and reproducible experiments
- Perform systematic error analysis and ablations to isolate failure modes (data vs model vs inference vs post-processing)
- Develop custom detection systems beyond standard training including multi-stage pipelines ensembles and specialized post-processing
- Optimize inference for latency throughput and memory including GPU acceleration and export toolchains
- Deliver production-grade services using Docker Linux CI/CD and APIs (FastAPI and/or gRPC)
- Implement testing strategy across the pipeline (unit integration regression) including golden image test sets
- Set up monitoring and maintenance: logging metrics dashboards drift/performance tracking retraining triggers
- Write clear technical documentation architecture decisions and trade-off analyses
- Read research papers and rapidly translate ideas into working prototypes and deployable components
Required Skills and Experience:
Python and ML Engineering
- Advanced Python engineering: clean architecture packaging typing testing profiling
- Strong PyTorch experience (must)
- TensorFlow optional
- Strong model debugging skills and disciplined experimentation
- Experiment tracking and reproducibility: W&B and/or MLflow deterministic runs seed control
- Config management: Hydra and/or OmegaConf
- Data pipelines: PyTorch Dataset/DataLoader augmentation pipelines caching
- Dataset versioning: DVC or equivalent
Computer Vision Fundamentals
- Strong CV fundamentals: preprocessing geometry photometric effects distortions camera models
- OpenCV expertise for classical CV and integration into modern ML pipelines
- Evaluation expertise: mAP precision/recall IoU PR curves calibration
Deep Object Detection Expertise
- Hands-on experience with modern detectors such as: YOLO (v5/v8/v9) Faster R-CNN RetinaNet EfficientDet DETR variants
- Experience building advanced detection workflows:
- Multi-stage detection (proposal refine classify)
- Ensemble and stacking strategies
- Specialized post-processing tuned to domain constraints
- Multi-stage detection (proposal refine classify)
Production ML and MLOps Delivery
- Model export and serving: ONNX export/runtime plus at least one of TorchScript or TensorRT
- GPU inference optimization and performance tuning (batching throughput latency memory)
- Deployment: Docker Linux CI/CD basics (GitHub Actions and/or GitLab CI)
- Service implementation: FastAPI and/or gRPC model versioning rollback strategy
- Monitoring and lifecycle: drift/performance monitoring logging dashboards retraining triggers
- Testing: unit tests for preprocessing/post-processing integration tests regression sets threshold stability tests
R&D Capability
- Ability to read papers and implement ideas quickly
- Strong debugging methodology ablation design and error analysis
- Clear technical writing and engineering decision-making
Nice-to-Have (Strong Bonuses)
Engineering Drawings Domain
- Experience with engineering drawings and technical documents
- PDF vector vs raster workflows line detection symbol detection
- Table/diagram understanding CAD-like concepts annotation workflows
- OCR vision hybrid systems (even if not OCR-first)
Document and Diagram Vision Toolchain
- PyMuPDF and/or pdfplumber
- Image rasterization coordinate transforms
- Handling noisy scans: skew/warp correction deskewing
Broader CV Capabilities
- Instance segmentation: Mask R-CNN YOLO-seg
- Keypoints pose landmark detection
- Tracking for video: ByteTrack DeepSORT
Key Skills
- APIs
- C/C++
- Computer Graphics
- Go
- React
- Redux
- Node.js
- AWS
- Library Services
- Assembly
- GraphQL
- High Voltage
