ML Engineer C2C requirements Location: SFO, CA (Hybrid)(

Role: ML Engineer
Location: SFO, CA (Hybrid)(Face to Face Interview Mandatory)
Contract

Key Responsibilities
Design, develop, and deploy machine learning models and algorithms
Build scalable data pipelines for training and inference
Collaborate with data scientists, engineers, and product teams
Optimize model performance, accuracy, and efficiency
Monitor, maintain, and improve models in production
Implement ML best practices (versioning, testing, monitoring)
Work with large datasets and perform feature engineering
Ensure models meet performance, reliability, and scalability requirements
Integrate ML solutions into applications via APIs or microservices
Required Skills & Qualifications
Strong programming skills (Python, Java, or C++)
Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Solid understanding of machine learning algorithms and statistics
Experience with data structures, algorithms, and software engineering principles
Familiarity with SQL and data processing tools (Spark, Hadoop)
Experience with cloud platforms (AWS, GCP, Azure)
Knowledge of MLOps tools (Docker, Kubernetes, CI/CD pipelines)
Ability to work with large-scale data and distributed systems
Preferred Qualifications
Experience deploying ML models in production environments
Knowledge of deep learning, NLP, or computer vision
Familiarity with model monitoring and drift detection
Experience with REST APIs and microservices architecture
Background in mathematics, statistics, or computer science
Key Tools & Technologies
Programming: Python, R, Java
ML Libraries: TensorFlow, PyTorch, Scikit-learn
Data Tools: Pandas, NumPy, Spark
Cloud: AWS, GCP, Azure
DevOps: Docker, Kubernetes, Git
MLOps: MLflow, Kubeflow, Airflow