Senior Machine Learning Engineer

Position- Senior Machine Learning Engineer
Location-Remote
12 Months Contract

Experience 10+ years of industry experience in Machine Learning, Deep Learning, and Computer Vision with a proven track record of designing, building, and deploying production-grade AI solutions at scale.
 
Please prioritize candidates with:
 
Strong hands-on experience with TensorFlow or PyTorch.
Extensive experience building and optimizing CNN-based computer vision models.
Experience with architecture selection/modification, transfer learning/backbones, hyperparameter tuning, model evaluation, and working with large-scale image datasets.
Proven production deployment and operational ownership of deep learning models.
 
Please de-prioritize candidates whose primary experience is:
Generative AI, Agentic AI, LLMs, RAG, NLP, or language modeling.
Traditional machine learning without deep learning.
Computer vision experience that is limited to using pre-built APIs or only academic/POC work.
 
Required
Technical Skills Machine Learning
- Strong understanding of supervised and unsupervised learning algorithms.
- Hands-on experience with regression, classification, clustering, ensemble learning, decision trees, random forests, and gradient boosting algorithms such as XGBoost, LightGBM, and CatBoost.
- Strong foundation in probability, statistics, hypothesis testing, experimental design, and statistical inference.
- Experience with feature engineering, model evaluation, cross-validation, bias-variance analysis, model calibration, and hyperparameter optimization. Deep Learning & Computer Vision - Strong expertise in TensorFlow (mandatory).
- Extensive experience training deep learning models from scratch on large-scale image datasets.
- Strong understanding of convolutional neural networks and modern computer vision architectures.
- Experience with image classification, object detection, semantic segmentation, instance segmentation, localization, embeddings, feature extraction, and image similarity.
- Experience designing custom neural network architectures, optimization techniques, loss functions, and distributed deep learning workflows. Production Machine Learning (Mandatory)
- Proven experience designing, deploying, and operating production machine learning systems.
- Experience building scalable machine learning training and inference pipelines.
- Experience with model registry, experiment tracking, model versioning, CI/CD for machine learning, and model monitoring.
- Experience designing data ingestion pipelines and managing large-scale datasets.
- Hands-on experience with distributed training and multi-GPU environments.
- Strong understanding of machine learning system scalability, performance optimization, and production reliability. Programming & Software Engineering
- Expert-level Python programming skills with experience building production-quality machine learning applications, reusable libraries, and scalable data processing pipelines.
- Strong understanding of software engineering principles, object-oriented design, design patterns, testing, debugging, performance optimization, and version control.
- Experience writing modular, maintainable, and production-quality code.
- Strong SQL and data analysis skills. Cloud & Infrastructure
- Hands-on experience with AWS SageMaker.
- Experience deploying machine learning workloads on AWS.
- Familiarity with cloud-native machine learning infrastructure and scalable training environments.