Tiger Analytics is looking to solve tough business challenges for Fortune 1000 companies by building next-generation machine learning platforms.
Requirements
- Proven, hands-on experience in building and deploying production-grade MLOps platforms.
- Strong expertise with the Databricks ecosystem for building scalable data and ML workflows.
- Extensive experience with at least one major cloud platform (AWS, GCP, or Azure) and its MLOps-related services.
- Deep understanding of the entire machine learning lifecycle, from data ingestion and feature engineering to model serving and monitoring.
- Proficiency in programming languages such as Python and experience with relevant ML libraries.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Certification in a relevant cloud platform (e.g., AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer)
Responsibilities
- Architect and Build MLOps Platforms: Lead the design and development of end-to-end MLOps platforms from the ground up, ensuring they are scalable, reliable, and secure.
- Client Management: Act as a primary technical point of contact for clients, managing expectations, communicating complex technical concepts clearly, and navigating challenging project requirements to ensure successful outcomes.
- Technical Leadership: Drive the technical vision for the MLOps practice, establishing best practices for model development, deployment, monitoring, and governance.
- Databricks Expertise: Leverage extensive, hands-on experience with Databricks to build and optimize data and machine learning pipelines.
- Cloud Integration: Design and implement solutions on one or more major cloud platforms (AWS, GCP, or Azure), utilizing their native services for data, compute, and machine learning.
- Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver integrated and high-value solutions.
Other
- 13+ years of professional experience in data engineering, machine learning, or software architecture, with a significant focus on MLOps.
- Demonstrated ability to handle challenging client management scenarios, acting as a trusted advisor and problem-solver.
- A background in traditional software development or software engineering principles.
- Significant career development opportunities exist as the company grows.
- The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
