Lead AIML Engineer / Associate Principal - ML Platform
Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Aug 12, 2026. Tiger Analytics scores B on the Alion truth index.
Sr. ML Platform Engineer
Exp : 6 -12 years
Location : Bangalore
Who we are
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.
Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.
We are a Great Place to Work-Certified™ (2022-26), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine.
Curious about the role? What your typical day would look like?
We are seeking an experienced AIML Engineer to design, lead, and implement advanced artificial intelligence and machine learning solutions. The ideal candidate will have deep expertise in machine learning frameworks, data pipelines, model lifecycle management, and cloud-based AI services.
What do we expect?
- 6-10 years of experience as a Backend Engineer, Platform Engineer, Senior ML Engineer, or similar role.
- Strong backend engineering skills in Python (and/or Java / Go) with experience building APIs and services.
- Strong system design skills: distributed systems, microservices, scalability, fault tolerance, reliability.
- Hands-on experience supporting Spark / PySpark and Airflow from a platform or operations perspective.
- Working knowledge of Azure ML pipelines, endpoints, and deployment patterns.
- Solid hands-on experience with Docker and Kubernetes (AKS preferred).
- Ability to debug complex production issues across application, data, and infrastructure layers.
- Experience designing or operating ML platforms or data platforms at scale.
- Familiarity with observability stacks such as Grafana, Prometheus, and Loki.
- Knowledge of event-driven architectures (Kafka, Azure Event Hub). - Exposure to Infrastructure-as-Code tools (Terraform, ARM).
- Experience working in vendor or managed-services engagement models.
You are important to us, let’s stay connected!
Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow.
We are an equal-opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.
Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.
Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities.