- Company Name
- Pennylane
- Job Title
- Machine Learning Manager
- Job Description
-
**Job Title:** Machine Learning Manager
**Role Summary:**
Lead a 5‑person team of Machine Learning and Data Engineers within Pennylane’s Data Department. Own the end‑to‑end machine learning lifecycle—from model design and training to deployment, inference, experimentation, and monitoring—while collaborating closely with Product, Data, and Software Engineering to deliver high‑impact solutions that enhance the user experience.
**Expectations:**
- **1 month:** Complete onboarding, learn product and tech stack, deliver small projects, start taking ownership of team and technical topics.
- **3 months:** Assume full responsibility for team and roadmap items, prioritize work autonomously, demonstrate proficiency with AWS, Terraform, streaming/batch pipelines, and data warehousing.
- **6 months:** Lead cross‑team initiatives, refine product and tech roadmaps, implement new processes and best practices.
- **Ongoing:** Recruit, mentor, and grow the ML team; elevate project leadership; continuously improve the ML ecosystem.
**Key Responsibilities:**
- Architect and implement scalable ML solutions across the entire ML lifecycle.
- Manage model training, hyper‑parameter tuning, deployment, inference, and production monitoring.
- Collaborate with Product Managers to align ML initiatives with business impact and user value.
- Work with Data and Software Engineers to build end‑to‑end data pipelines and production systems.
- Set and enforce engineering practices, coding standards, and quality gates for ML work.
- Mentor team members, conduct performance reviews, and drive career development.
- Define and execute team roadmap, balancing short‑term deliverables with long‑term growth.
- Foster a culture of experimentation, continuous learning, and data‑driven decision making.
**Required Skills:**
- Strong experience in ML engineering (model development, deployment, monitoring).
- Proficiency with data engineering tools (ETL, streaming, batch, scheduling, data warehousing).
- Hands‑on experience with AWS services, Terraform, and CI/CD pipelines for ML.
- Leadership and people‑management skills: hiring, mentoring, performance management.
- Excellent communication, stakeholder management, and cross‑functional collaboration.
- Ability to translate business requirements into technical solutions and measurable outcomes.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, TensorFlow Developer Certificate, or equivalent) are a plus.