Overview:
TekWissen is a global workforce management provider throughout India and many other countries in the world. The below job opportunity is to one of our clients who is a part of a trusted global innovator of IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, IT modernization and managed services. This client enables us to move confidently into the digital future. This client committed to Long Term success and combine global reach with local client attention to serve them in over 50 Countries.
Position: MLE - Lead
Location: Chennai / Pune
Work Type: Hybrid
Job Type: Full Time
- Lead Machine Learning Engineer – Python, ML Frameworks, MLOps, Containerization, Terraform, GCP, Vertex AI, IBM Watsonx
About Machine Learning Engineering at UPS Technology:
- We’re the obstacle overcomers, the problem get-arounders. From figuring it out to getting it done our innovative culture demands “yes and how!” We are UPS. We are the United Problem Solvers.
- Our Machine Learning Engineering teams use their expertise in data science, software engineering, and AI to build next-generation intelligent systems.
- These systems power our Smart Logistics Network, optimize UPS Airlines, and enhance Global Transportation Operations. We build scalable, production-grade ML solutions that move up to 38 million packages a day (4.7 billion annually), delivering measurable impact across the enterprise
About this Role:
- We are seeking a visionary
Lead Machine Learning Engineer
to architect, guide, and deliver enterprise-grade ML solutions that drive strategic business outcomes. - You will lead cross-functional teams, define technical direction, and ensure the robustness, scalability, and reliability of ML systems across the full lifecycle.
- As a Lead MLE, you will play a pivotal role in shaping our ML platform strategy, mentoring senior engineers, and driving adoption of best practices in MLOps, model governance, and responsible AI.
- You’ll collaborate with stakeholders across data science, engineering, and product to translate complex business challenges into intelligent systems.
Key Responsibilities:
Lead the design
, development, and deployment of scalable ML models and pipelines for high-impact business applications.- Architect ML systems using Vertex AI Pipelines, Kubeflow, Airflow, and manage infrastructure-as-code with Terraform/Helm.
- Define and implement strategies for automated retraining, drift detection, and model lifecycle management.
- Oversee CI/CD workflows for ML, ensuring reliability, reproducibility, and compliance.
- Establish standards for model monitoring, observability, and alerting across accuracy, latency, and cost.
- Drive integration of feature stores, vector databases, and knowledge graphs for advanced ML/RAG use cases.
- Ensure security, compliance, and cost-efficiency across ML pipelines and infrastructure.
Champion MLOps best practices
and lead initiatives for reproducibility, versioning, lineage tracking, and governance.Mentor and coach
senior/junior engineers, fostering a culture of technical excellence and innovation.- Stay ahead of
emerging ML technologies
and evaluate their applicability to UPS’s ecosystem. - Collaborate with leadership, product managers, and domain experts to align ML initiatives with strategic goals.
- Contribute to long-term ML platform architecture and roadmap planning.
Required Qualifications:Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD preferred).
Experience
- 8+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.
- Proven track record of leading ML projects from conception to production.
Deep expertise in Python
(scikit-learn, PyTorch, TensorFlow, XGBoost) and SQL.- Experience
architecting ML systems
in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML). - Strong background in
containerization
(Docker, Kubernetes),orchestration
(Airflow, TFX, Kubeflow), and infra-as-code
(Terraform/Helm). - Experience in
big data and streaming technologies
(Spark, Flink, Kafka, Hive, Hadoop). - Hands-on experience with model observability tools (Prometheus, Grafana, EvidentlyAI) and Governance platforms (WatsonX).
- Strong understanding of ML algorithms, deep learning architectures, and statistical methods.
- Demonstrated leadership in mentoring teams and influencing technical direction.
Preferred Qualifications:
- Experience with real-time inference systems or low-latency streaming platforms.
- Hands-on with enterprise ML platforms
(IBM WatsonX, GCP Vertex AI)
and feature stores. - Knowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn).
- Expertise in data/model governance, lineage tracking, and compliance frameworks.
- Contributions to open-source ML/MLOps libraries or active participation in ML communities.
- Domain experience in logistics, supply chain, or large-scale consumer platforms.
- Experience presenting technical solutions to executive stakeholders.
TekWissen® Group is an equal opportunity employer supporting workforce diversity
