Sr Lead AI/ML Engineer

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 scale ML pipelines. You will lead end-to-end inference, implement deep learning for forecasting, and integrate ML components into service-oriented architectures.

You will work with streaming technologies like Kafka, collaborate with agile teams, and ensure reproducibility using Git and container platforms. Office-based role at Manyata Tech Park, Bangalore.

Qualifications

• 6–8 years of experience building modern software applications.
• At least 5 years building ML pipelines with Java, Python or Scala.
• 4 years with distributed computing: Spark, DASK or Ray.
• Strong skills in ML frameworks and real-time streaming.
• Experience with RESTful services and containerization.

Responsibilities

• Design, develop, and maintain scalable ML pipelines in Java, Python, or Scala.
• Deploy distributed computing solutions with Spark, DASK, or Ray.
• Lead end-to-end low-latency inference in production.
• Build deep learning pipelines for forecasting and personalization.
• Collaborate with agile teams to implement RESTful services and SOA.
• Utilize Kafka or Storm for real-time data ingestion and processing.
• Drive experimentation, model evaluation, and statistical analysis.
• Ensure reproducibility with Git, Jira, and Docker/PCF.

Skills

Java

Python

Scala

Spark

DASK

Ray

TensorFlow

PyTorch

Sci-Kit Learn

Keras

MXNet

Statistics

Hypothesis Testing

T-Test

Z-Test

Regression

Kafka

Storm

REST

SOA

Docker

PCF

KubeFlow

BentoML

Git

Education

Bachelor's degree

TensorFlow Developer Certificate

Databricks Certified Associate Developer for Apache Spark

Tools

Great Expectations

Evidently AI

KubeFlow

BentoML

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

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. Bachelors 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)

This role requires working from the office at Manyata Tech Park, Bangalore, for at least 4 days per week.