Senior Machine Learning Engineer
- Posted 12 days ago
- Be among the first 10 applicants
Job Description
Role Overview:
We are seeking a highly experienced Senior Machine Learning Engineer with a strong engineering foundation and deep expertise in building, deploying, and scaling Machine Learning and Generative AI solutions in production environments.
The ideal candidate will have 5+ years of experience across the complete ML lifecycle, from data acquisition and model development to MLOps, deployment, monitoring, and business impact measurement. The candidate should have demonstrated success in delivering commercial AI products and building production-grade AI applications leveraging modern LLMs and Generative AI frameworks.
Key Responsibilities:
Machine Learning & Data Science
- Design, develop, and deploy end-to-end ML solutions at scale.
- Build and optimize predictive models, recommendation systems, NLP solutions, and deep learning applications.
- Drive the complete data science lifecycle:
- Problem formulation
- Data exploration
- Feature engineering
- Model training
- Evaluation
- Production deployment
- Monitoring and retraining
Generative AI
- Build enterprise-grade GenAI applications using:
- OpenAI
- Azure OpenAI
- Anthropic Claude
- Llama
- Mistral
- Gemini
- Design and implement:
- RAG architectures
- Agentic AI systems
- Multi-agent frameworks
- Prompt engineering strategies
- Fine-tuning pipelines
Key Responsibilities:
- Design, build, deploy, and monitor production-grade ML solutions
- Develop AI/ML applications using modern ML and GenAI frameworks
- Build and optimize end-to-end ML pipelines
- Collaborate with Product and Engineering teams to deliver business impact
- Drive best practices in MLOps, model governance, and scalability
Preferred Skills:
- Python, SQL, Spark
- ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)
- LLMs, RAG, Agentic AI
- Docker, Kubernetes, Cloud Platforms (AWS/Azure/GCP)
- MLOps and model deployment
More Info
Job Type:
Industry:
Employment Type:
Key Skills
About Company
Skills:
model development , Data Cleaning, Sql, Numpy, Pandas, Python, offline evaluation, time-series data anomaly detection, scikit-learn, field validation, Forecasting, Classification, hybrid ML plus heuristics, Regression, rule-based systems, deployment monitoring, signal validation, drift detection, feature engineering
Skills:
state estimation , Vision-Language Models (VLMs), Pytorch, Opencv, ROS, Python, Computer Vision, SLAM, Isaac Sim, MuJoCo, Gazebo, TensorRT, LibTorch, RT-2, OpenVLA, Eigen, ?0, ONNX Runtime, Transformers, Motion Planning, perception, ROS2, Imitation Learning
Skills:
Golang, Jax, Prometheus, Cloudwatch, Grafana, Tensorflow, Pytorch, Python, Java, Scala, MLops, Spark, Keras, Kubernetes, Scalable ML architectures, End-to-end machine learning pipelines, Automated remediation, MLflow, Prediction and drift monitoring, Model hosting, Stream processing pipelines, Big data frameworks, Model versioning, API performance monitoring, Embedding scaling, Feature stores, Data versioning
Skills:
Bi Tools, Data Analytics, Deep Learning, Tensorflow, Pytorch, MLops, Gcp, Docker, Excel, Azure, Python, Kubernetes, AWS, Generative AI, ML algorithms, NLP frameworks, MLflow, Scikit-Learn, Statistical Modeling, Kubeflow, Data ML pipelines
Skills:
error analysis , Deduplication, Pytorch, Python, Cloud Storage, Statistical Analysis, data augmentation, model training, model-based labeling, distributed compute, Active Learning, VLMs, Hugging Face LLMs, ablation studies, dataset curation, benchmark evaluation, workflow orchestration, weak supervision, Batch Processing, inference evaluation, synthetic-data generation, Production Monitoring, data-quality measurement, diffusion models, multimodal models