---
title: 'Senior Lead AI/ML Engineer - R01570774 at Brillio'
canonical: 'https://feeny.ai/job/senior-lead-ai-ml-engineer-r01570774-brillio-bengaluru-8zzca7scmpg1'
type: 'job'
last_seen: '2026-10-18'
---

# Senior Lead AI/ML Engineer - R01570774 at Brillio

- **Company:** Brillio
- **Location:** Bengaluru, India
- **Posted:** 2026-10-16
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.lever.co/brillio-2/0938c93c-7da5-424e-9e16-67a3bbe2d6ed

## Job description

Senior Lead AI/ML Engineer

Primary Skills

- Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio

Job requirements

- Experience Range: 6 to 8 years of experience developing modern software applications, including at least 5 years building and optimizing machine learning pipelines with Java, Python, or Scala, and 4 years working with distributed computing frameworks such as Spark, DASK, or Ray. Key Responsibilities: 1. Design, develop, and maintain scalable machine learning pipelines using Java, Python, or Scala to support advanced data science solutions. 2. Implement, optimize, and deploy distributed computing solutions leveraging frameworks such as Spark, DASK, or Ray to handle large-scale data processing and model training. 3. Lead the end-to-end delivery of low-latency inferencing solutions, ensuring robust performance and reliability in production environments. 4. Build and enhance deep learning pipelines for forecasting and personalization using frameworks such as PyTorch and TensorFlow. 5. Collaborate with cross-functional agile teams to design and implement RESTful web services and integrate machine learning components into broader service-oriented architectures. 6. Utilize real-time streaming technologies like Kafka or Storm to enable real-time data ingestion and processing for machine learning applications. 7. Drive experimentation, model evaluation, and statistical analysis using advanced techniques such as hypothesis testing, regression, and probabilistic graphical models. 8. Ensure quality and reproducibility of machine learning workflows by leveraging tools such as Git, JIRA, and containerization platforms like Docker or PCF. Required Skills: 1. Advanced proficiency in Java, Python, or Scala for software and ML pipeline development 2. Hands-on experience with distributed computing frameworks such as Apache Spark, DASK, or Ray 3. Deep understanding of machine learning frameworks including TensorFlow, PyTorch, Sci-Kit Learn, Keras, and MXNet 4. Expertise in statistical analysis and computing, including hypothesis testing, T-Test, Z-Test, and regression methods 5. Experience with real-time data streaming tools such as Kafka or Storm 6. Knowledge of building and deploying deep learning models for forecasting and personalization 7. Proficiency in RESTful web services and service-oriented architecture design 8. Experience with containerization technologies such as Docker or PCF 9. Familiarity with ML workflow orchestration tools like KubeFlow or BentoML 10. Proficiency with Git for version control Preferred Skills: 1. Experience with Great Expectations or Evidently AI for model monitoring and validation 2. Hands-on expertise in SAS, SPSS, or R/R Studio for advanced statistical modeling 3. Knowledge of advanced forecasting techniques including Exponential Smoothing, ARIMA, and ARIMAX 4. Familiarity with classification algorithms such as Decision Trees and SVM 5. Understanding of distance metrics like Hamming, Euclidean, and Manhattan Distance 6. Experience in container orchestration and deployment within cloud or hybrid environments 7. Experience using agile project management tools such as JIRA Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Systems, Data Science, or a closely related field 2. Relevant certification in machine learning, data engineering, or distributed computing (such as TensorFlow Developer Certificate or Databricks Certified Associate Developer for Apache Spark) Additional Information: This role requires working from the office at Manyata Tech Park, Bangalore, for at least 4 days per week.

## About Brillio

## Company Overview
- **One-liner**: Brillio is a digital transformation consulting and technology services company that helps Fortune 1000 enterprises accelerate AI adoption and scale impact through its AI accelerator platform, ADAM.
- **Entity Type**: Private (backed by Bain Capital Private Equity)
- **Headquarters**: Dallas, Texas, United States
- **Founded**: 2014
- **Founders**: Not publicly disclosed (CEO: Raj Mamodia)

## Core Business
- **Primary industries**: IT Services and IT Consulting; Digital Transformation; AI and Data Engineering; Customer Experience Transformation; Digital Engineering; Infrastructure Engineering
- **Target customers**: Fortune 1000 enterprises (B2B, Enterprise)
- **Mission / purpose statement**: “The Enterprise AI Accelerator” – helping companies move from AI ambition to scaled impact, faster.

## Products & Services
- **ADAM (Agentic Data and Application Management)**: A self-service LLM model garden and GenAI platform for building, testing, and deploying over a hundred GenAI use cases at scale. Core accelerator for Brillio’s delivery.
- **Business-led transformation**: Strategy consulting and business process modernization.
- **Customer experience transformation**: Design, digital product engineering, and omnichannel experience.
- **AI and data engineering**: Predictive models, enterprise search, RAG systems, AI copilots, autonomous agents, multi-agent workflows.
- **Digital engineering**: Application modernization, platform engineering, cloud-native development.
- **Infrastructure engineering**: Cloud infrastructure, security, MLOps/LLMOps, and observability.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (privately held)
- **Key Metric**: Annual revenue reported at **$1B** (latest available); total employees ~3,941 (+6.7% YoY) per LinkedIn, though company claims “over 6,000 customer-obsessed professionals” on its website.
- **Notable Investors / Partners**: Bain Capital Private Equity (parent company); Great Place to Work® certified in the USA.
- **Growth Signals**: +352 employees YoY; 14 delivery locations across North America, Europe, and Asia; expanding AI engineering roles; 616,797 LinkedIn followers (+24.4% yearly growth).

## Competitive Advantages
- **Enterprise AI focus**: Industrializing AI across every layer of the business – not just building demos but shipping production systems.
- **ADAM platform**: Proprietary accelerator that enables rapid deployment of GenAI use cases, shortening time-to-value for clients.
- **End-to-end ownership**: Engineers design, build, evaluate, and run agentic and GenAI systems that reach live users.
- **Scale and reach**: Global delivery footprint (USA, India, UK, Europe, Mexico, Canada, Romania) with deep Fortune 1000 client relationships.

## Strategic Focus
- **AI engineering at scale**: Moving AI from pilots to production with a focus on agentic systems, LLMOps, evaluation, security, and governance.
- **Continuous learning**: Brillio Academy, hackathons, mentoring, and certifications to keep skills current.
- **Talent development**: Hiring based on demonstrated ability (not just degrees); clear career paths from engineer to AI architect or technical leadership.
- **Diversity & inclusion**: Committed to a diverse, inclusive workplace; no discrimination based on protected characteristics.

## Why Work Here
- **Culture**: Rated 4.0/5.0 on Glassdoor (2,264 reviews) and 4.0/5.0 on LinkedIn; 80% would recommend to a friend; Great Place to Work® certified in the USA.
- **Work environment**: Engineers get meaningful ownership within clear guardrails – autonomy to make architecture and trade-off calls on their workstreams.
- **Learning & growth**: Brillio Academy, hackathons, personalized career development framework; exposure to cutting-edge GenAI and agentic AI projects.
- **Remote / hybrid / office**: Not explicitly stated, but global delivery locations suggest a mix of on-site and remote (roles posted across multiple countries).
- **Benefits**: “BYou” wellness program built on four pillars of wellness – personal and professional well-being and development.
- **Interview process**: Focus on software fundamentals, LLMs, RAG, agents, evaluation, and a design or debugging exercise; candidates should be ready to walk through a real system they shipped.

## Sources
1. [careers.brillio.com](https://careers.brillio.com/)
2. [brillio.com/about-us/who-we-are](https://www.brillio.com/about-us/who-we-are/)
3. [linkedin.com/company/brillio](https://linkedin.com/company/brillio)
4. [glassdoor.com/Reviews/Brillio-Reviews-E821879](https://www.glassdoor.com/Reviews/Brillio-Reviews-E821879.htm)
5. [wikipedia.org/wiki/Brillio](https://en.wikipedia.org/wiki/Brillio)

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