Prove is looking for a Senior Machine Learning Engineer to bridge the gap between data science and software engineering, ensuring machine learning models are production-ready, monitored, and continuously improved to enhance security, reduce friction, and accelerate revenue for their clients.
Requirements
- Strong programming skills in Python (and experience with libraries such as scikit-learn, TensorFlow, or PyTorch), Java, and/or Go.
- Hands-on experience building APIs and services (e.g., FastAPI, Flask, gRPC).
- Expertise with containerization & orchestration (Docker, Kubernetes).
- Familiarity with CI/CD pipelines and modern MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, or similar).
- Strong understanding of cloud platforms (AWS).
- Solid background in data pipelines, distributed systems, and performance optimization.
- 5-7+ years of professional experience in ML engineering, software engineering, or related roles.
Responsibilities
- Collaborate with data scientists to transform research models into production-ready services.
- Design, build, and maintain APIs and microservices to serve ML models at scale.
- Ensure smooth integration of ML solutions into core products and platforms.
- Optimize inference performance, latency, and scalability.
- Build monitoring, logging, and alerting systems to track model performance and data drift.
- Implement retraining pipelines and automated workflows for continuous improvement.
- Develop CI/CD pipelines for machine learning workflows.
Other
- Work closely with cross-functional teams to align model capabilities with business needs.
- Mentor junior engineers and contribute to best practices in ML engineering.
- Advocate for scalable, sustainable ML deployment strategies across the organization.
- Strong collaboration skills with both data scientists and software engineers.
- Ability to balance technical rigor with pragmatic delivery.
