Sr. Machine Learning Engineer
Posted Updated
Description
Responsibilities:
- Lead engineering initiatives aimed at the continuous enhancement of the ML platform and build high-quality models to drive value for users and our company.
- Hands-on contributor and overseer of ML workflow to build scalable, robust, distributed infrastructure to support machine learning training, inference, and evaluation.
- Evaluate the technical tradeoffs of every decision.
- Perform code reviews and ensure exceptional code quality.
- Mentor and guide junior engineers, fostering a culture of growth, collaboration, and innovation within the technical team.
- Iterate quickly without compromising quality.
Requirements:
- Bachelor's Degree in a relevant technical field, such as computer science, and 6+ years of post-bachelor's machine learning experience; or Master's degree in a technical field + 5+ years of post-grad machine learning experience; or PhD in a relevant technical field + 3 years of post-grad machine learning experience.
- Experience developing machine learning models for supervised, unsupervised, ranking, or other relevant applications of machine learning.
- Strong understanding of machine learning approaches and algorithms.
- Have a track record in deploying scaled ML systems.
- Experience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks.
- Strong communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
- Experience in cross-functional team alignment and collaborating closely with domain experts, engineers, and product specialists.
- Entrepreneurial Mindset: Highly motivated and adaptable with a passion for innovation, problem-solving, and making a meaningful impact in a startup environment. Willingness to take ownership and drive projects from concept to implementation.
Preferred to have:
- Experience in on-prem ML model deployment and observability.
- Experience in building and deploying ML models for real-time time series data like sensor/IoT data.