Job Title: Machine Learning Engineer
Location: California (CA)
Duration: 12+ Months
Employment Type: W2 Contract Only
Job Description
We are seeking an experienced Machine Learning Engineer to join our team on a long-term project. The ideal candidate has a strong background in building, deploying, and optimizing ML models, along with expertise in cloud platforms and MLOps. You will work closely with data scientists, engineers, and product stakeholders to deliver scalable and production-ready ML solutions.
Responsibilities
- Design, build, and deploy scalable ML models for real-world applications (NLP, CV, recommendation systems, etc.).
- Develop and maintain ML pipelines, including data preprocessing, feature engineering, training, and model serving.
- Work with large-scale structured and unstructured data to ensure accuracy and efficiency.
- Deploy and monitor ML models in production using AWS/GCP/Azure ML environments.
- Apply MLOps best practices for automation, CI/CD, model retraining, and monitoring.
- Collaborate with cross-functional teams to translate business problems into ML solutions.
- Conduct experiments, model tuning, and A/B testing to optimize performance.
- Stay current with the latest ML frameworks, research, and technologies.
Required Skills
- 8+ years of professional experience in machine learning / AI engineering.
- Strong programming skills in Python with ML/DL libraries (TensorFlow, PyTorch, scikit-learn).
- Solid understanding of ML algorithms, optimization, and statistical methods.
- Experience with data engineering tools (Spark, Airflow, SQL).
- Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
- Proficiency in MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).
- Strong knowledge of CI/CD, Git, and containerization.
