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Machine Learning Engineer IV (Computer Vision)
HuntingCube Recruitment Solution
Not specified · onsite · Posted 28d ago
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Section · 01
About this role
Job Description
What You'll Do
[PyTorch, Python, Machine Learning]
Additional Information
NA
What You'll Do
- Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)
- Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
- Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX
- Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.
- Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.
- Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.
- Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis.
- Deep expertise in computer vision and biometrics, especially face recognition.
- Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.
- Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code.
- Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.
- Cloud Native: Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).
- Research Publications: Papers in CVPR, ICCV, ECCV, or FG related to face recognition, image quality assessment, or fairness.
- Large Scale Search: Experience with vector databases (e.g., Milvus, Faiss) and approximate nearest neighbor (ANN) search algorithms.
- Familiarity with privacy, security, and compliance in biometric systems.
- Mobile/Edge Experience: Experience porting models to edge or mobile devices utilizing frameworks such as CoreML, LiteRT, and/or TFLite.
- Synthetic Data: Experience using GANs or diffusion models to generate synthetic faces for training.
- Strong communication skills.
[PyTorch, Python, Machine Learning]
Additional Information
NA
Sourced from foundit
Section · 02
Skills
amazon web servicesapache airflowOpencvTensorRTOnnxPillowJAXPytorchTensorflowPythonMachine Learning
Section · Company
About HuntingCube Recruitment Solution
HuntingCube Recruitment Solution
Recruitment
300
employees
2015
11 years old
Noida, Uttar Pradesh
IN
₹3.5L PA avg
Avg at HuntingCube Recruitment Solution
About
HuntingCube is a fast-growing recruitment firm, founded by Mayank Tiwari,Anshuman Gupta & Ashwani Singh, specializing in hiring top talent for India’s leading product companies & high-growth startups.
Industries
RecruitmentIT Services & Consulting
Employee ratings
10 reviews
3.8/ 5
Culture
3.1
Career growth
3.0
Work-life
3.2
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