Production Machine Learning Engineer deploying advanced perception models in Toyota's autonomous vehicle platform. Join a team innovating in mobility solutions while ensuring safety and reliability.
About the role
- Software Engineer developing and scaling machine learning systems for a consumer finance platform. Collaborating with data engineers and deploying models in cloud environments.
Responsibilities
- Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference.
- Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies.
- Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques.
- Work with structured and unstructured data, leveraging Pandas, NumPy, and SQL for efficient data manipulation.
- Apply machine learning design patterns to build modular, reusable, and production-ready models.
- Collaborate with data engineers to develop high-performance data pipelines for training and inference.
- Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes.
- Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.
Requirements
- Proficiency in Python and familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch.
- Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for tracking experiments and automating workflows.
- Hands-on experience with data manipulation libraries (Pandas, NumPy) and databases (SQL, NoSQL).
- Knowledge of cloud-based ML deployment and infrastructure management.
- Ability to implement real-time and batch inference pipelines efficiently.
- Strong analytical and problem-solving skills to translate business needs into scalable ML solutions.
- Eagerness to work in a fast-paced environment and continuously refine ML processes for efficiency and accuracy.
Benefits
- $250 monthly lunch stipend
- $150 monthly commuter stipend
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer at Amex GBT utilizing AI techniques for business travel solutions. Collaborating globally to design, build, and optimize intelligent systems with measurable impact.
Machine Learning Engineer empowering clinicians through data - driven innovations at SimplePractice. Building AI workflows and optimizing models for effective patient care delivery with a hybrid work approach.
Backend Engineer optimizing ML infrastructure to enhance performance at an energy forecasting startup. Collaborating with ML engineers to improve tooling and infrastructure for large - scale data processing.
Machine Learning Engineer responsible for designing AI applications leveraging Generative AI and LLMs at Citi. Involves architecting scalable platform services and collaborating with cross - functional teams.
Develop and validate machine learning models at PayPal for innovative AI/ML solutions. Collaborate with data scientists and software engineers to enhance services and customer experiences.
Machine Learning Engineer at PayPal validating and developing models to solve complex problems. Collaborating with engineers and data scientists for innovative AI/ML solutions.
Middle/AI/ML Engineer developing LLM - based extraction pipelines and influencing platform evolution. Building systems to enhance hiring intelligence through data processing and transformation.
AI/ML Engineer for Aily Labs building robust AI/ML systems and scalable infrastructure. Collaborating with teams to empower business - critical decision - making.
Principal Machine Learning Engineer at Coinbase working on building onchain platform and future financial systems. Seeking a passionate candidate with experience in machine learning for crypto and blockchain technology.