Senior Lead AI/ML Engineer - R01570774

Brillio; Bengaluru; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Brillio is seeking a Senior Lead AI/ML Engineer to design and deliver scalable ML pipelines and real-time data processing at scale. The role emphasizes end-to-end development from model training to production inference in a Java/Python/Scala environment.

You will lead cross-functional teams, optimize distributed pipelines, and integrate ML components into RESTful services. Office-based work in Bengaluru for four days weekly is expected.

Qualifications

• 6–8 years building software with ML pipelines.
• 5+ years optimizing ML pipelines in Python/Java/Scala.
• 4+ years with distributed computing (Spark, DASK, or Ray).
• Strong knowledge of TF, PyTorch, and ML frameworks.

Responsibilities

• Design, develop, and maintain scalable ML pipelines in Java/Python/Scala.
• Deploy distributed computing solutions for large-scale data processing.
• Lead end-to-end low-latency inferencing in production.
• Build deep learning pipelines for forecasting/personalization (PyTorch/TensorFlow).
• Integrate ML components with RESTful services and SOA.
• Use Kafka/Storm for real-time data ingestion and processing.
• Drive experimentation, model evaluation, and statistical analysis.
• Ensure reproducibility with Git, JIRA, Docker/PCF.

Skills

Java

Python

Scala

Spark

DASK

Ray

TensorFlow

PyTorch

Sci-Kit Learn

Keras

MXNet

Kafka

Storm

RESTful services

Docker

PCF

KubeFlow

BentoML

Git

Education

Bachelor's degree in Computer Science/Information Systems/Data Science

ML/distributed computing certifications (TensorFlow Dev Certificate, Databricks Spark)

Tools

Spark

DASK

Ray

TensorFlow

PyTorch

Scikit-Learn

Keras

MXNet

Kafka

Storm

Docker

PCF

KubeFlow

BentoML

Git

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

• Design, develop, and maintain scalable machine learning pipelines using Java, Python, or Scala to support advanced data science solutions.
• Implement, optimize, and deploy distributed computing solutions leveraging frameworks such as Spark, DASK, or Ray to handle large-scale data processing and model training.
• Lead the end-to-end delivery of low-latency inferencing solutions, ensuring robust performance and reliability in production environments.
• Build and enhance deep learning pipelines for forecasting and personalization using frameworks such as PyTorch and TensorFlow.
• Collaborate with cross-functional agile teams to design and implement RESTful web services and integrate machine learning components into broader service-oriented architectures.
• Utilize real-time streaming technologies like Kafka or Storm to enable real-time data ingestion and processing for machine learning applications.
• Drive experimentation, model evaluation, and statistical analysis using advanced techniques such as hypothesis testing, regression, and probabilistic graphical models.
• Ensure quality and reproducibility of machine learning workflows by leveraging tools such as Git, JIRA, and containerization platforms like Docker or PCF.

Required Skills

• Advanced proficiency in Java, Python, or Scala for software and ML pipeline development
• Hands-on experience with distributed computing frameworks such as Apache Spark, DASK, or Ray
• Deep understanding of machine learning frameworks including TensorFlow, PyTorch, Sci-Kit Learn, Keras, and MXNet
• Expertise in statistical analysis and computing, including hypothesis testing, T-Test, Z-Test, and regression methods
• Experience with real-time data streaming tools such as Kafka or Storm
• Knowledge of building and deploying deep learning models for forecasting and personalization
• Proficiency in RESTful web services and service-oriented architecture design
• Experience with containerization technologies such as Docker or PCF
• Familiarity with ML workflow orchestration tools like KubeFlow or BentoML
• Proficiency with Git for version control

Preferred Skills

• Experience with Great Expectations or Evidently AI for model monitoring and validation
• Hands-on expertise in SAS, SPSS, or R/R Studio for advanced statistical modeling
• Knowledge of advanced forecasting techniques including Exponential Smoothing, ARIMA, and ARIMAX
• Familiarity with classification algorithms such as Decision Trees and SVM
• Understanding of distance metrics like Hamming, Euclidean, and Manhattan Distance
• Experience in container orchestration and deployment within cloud or hybrid environments
• Experience using agile project management tools such as JIRA

Desired Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, or a closely related field
• 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.