Role - Machine Learning Engineer
Location - San Francisco, CA(hybrid)
W2 Only
Job Description:
We are looking for a talented Machine Learning Engineer to design, develop, and deploy ML models that drive business insights and automation. The ideal candidate will have a solid foundation in ML techniques along with decent Data Engineering skills and hands-on experience with big data tools such as Spark and Hadoop to handle large-scale data processing.
Key Responsibilities:
- Develop, test, and deploy machine learning models and algorithms
- Collaborate with data scientists and data engineers to optimize data workflows
- Build and maintain scalable data pipelines for training and inference using Spark, Hadoop, and other big data tools
- Perform data preprocessing, feature engineering, and exploratory data analysis
- Monitor model performance and fine-tune models as needed
- Implement best practices for model deployment and versioning
- Stay updated with the latest ML research and industry trends
Mandatory Skills and Qualifications:
- Strong understanding of machine learning algorithms and frameworks (TensorFlow, PyTorch, scikit-learn, etc.)
- Solid Data Engineering skills, including ETL, data pipelines, and SQL
- Hands-on experience with big data tools such as Spark and Hadoop
- Proficiency in Python
- Familiarity with cloud platforms (AWS, Azure, GCP) is a plus
- Good problem-solving and communication skills
Preferred Skills:
- Experience with containerization and deployment (Docker, Kubernetes)
- Knowledge of MLOps practices and tools