Job Description
Ovii's Interpretation of the Role
Lead the design and delivery of large‑scale machine learning platforms for Tekion’s cloud‑native automotive suite. Drive MLOps standards, mentor senior engineers, and partner with product and data science teams to ship reliable, high‑impact ML solutions.
Role Snapshot
- Architect large‑scale ML platforms
- Define MLOps best practices
- Mentor senior engineers
- Collaborate with data science & product
- Optimize real‑time and batch inference
Must-Have Requirements
- Python
- TensorFlow / PyTorch / Scikit‑learn
- Distributed systems
- AWS / GCP / Azure
- Kubernetes
- MLOps tools and practices
- software engineering
- machine learning engineering
- leadership and architecture
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field
Work Setup
- Location: Bangalore, India
- Work mode: ONSITE
- Employment type: Full-Time
Eligibility Gates
- Visa sponsorship: unknown
Not Specified in JD
- Visa sponsorship
- Salary range
- Remote eligibility
- Equity
- Bonus
- Notice period
- Travel
- Security clearance
- Coding test
- Portfolio
- GitHub
- Writing sample
- Cover letter
What You'll Likely Work On
- Architect and lead development of scalable ML platforms supporting training, deployment, and lifecycle management
- Partner with data science, applied science, and product teams to productionize models with performance, reliability, and compliance
- Establish MLOps pipelines including model versioning, automated retraining, monitoring, and CI/CD workflows
- Guide technical decisions to ensure scalability, security, and maintainability of ML infrastructure
- Optimize inference pipelines for both real‑time and batch workloads across cloud and hybrid environments
- Advise leadership on architectural strategy and ML infrastructure investments
- Mentor senior engineers and elevate technical capability across the organization
- Evaluate emerging technologies and frameworks to advance the ML engineering roadmap
Good Fit If You Have
- Strong communication and collaboration skills
- Experience influencing cross‑functional architectural strategy
- Passion for building production‑grade ML systems at scale
Skills
- Python
- ML frameworks (TensorFlow, PyTorch, Scikit‑learn)
- Distributed systems design
- Cloud platforms (AWS, GCP, Azure)
- Kubernetes orchestration
- MLOps tooling & CI/CD
- Model performance monitoring
- Technical leadership & mentorship