Senior Machine Learning Engineer

Salary- $150,000

Location- San Francisco Bay Area

Hybrid- 2-3 days in office per week

About Us

We are seeking an exceptional Machine Learning Engineer to join our clients growing AI team. As a key member of our clients organization, you'll be responsible for developing and deploying cutting-edge machine learning solutions that drive business value and innovation.

Core Responsibilities

• Design, develop, and implement scalable machine learning models and algorithms
• Collaborate with cross-functional teams to identify and solve complex business problems using ML/AI solutions
• Build and maintain ML pipelines for data preprocessing, model training, and deployment
• Optimize existing models and systems for maximum efficiency and accuracy
• Conduct A/B tests and experiments to measure model performance
• Stay current with latest ML research and technologies, evaluating their potential application
• Mentor junior team members and contribute to technical documentation

Required Qualifications

• Master's or Ph.D. in Computer Science, Mathematics, Statistics, or related field
• 3+ years of hands-on experience developing and deploying ML models in production
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with deep learning, natural language processing, and/or computer vision
• Solid understanding of ML fundamentals, including supervised/unsupervised learning, neural networks, and optimization techniques
• Expertise in data structures, algorithms, and software engineering best practices
• Experience with ML deployment tools and MLOps practices (Docker, Kubernetes, CI/CD)
• Strong command of version control systems (Git) and collaborative development

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, or Azure)
• Knowledge of distributed computing and big data technologies (Spark, Hadoop)
• Contributions to open-source ML projects or research publications
• Experience with ML model monitoring and maintenance in production
• Familiarity with modern AI frameworks and large language models

Technical Skills

• Programming Languages: Python, SQL
• ML Frameworks: PyTorch, TensorFlow, scikit-learn
• Cloud Platforms: AWS/GCP/Azure
• MLOps Tools: Docker, Kubernetes, MLflow
• Version Control: Git
• Big Data: Spark, Hadoop (preferred)