Staff Product Software Engineer

The Walt Disney Company; Bengaluru; On-site; INR 4,000,000 - 6,400,000; Full time

Job summary

The Walt Disney Company in Bengaluru is seeking an experienced ML engineering leader to own end-to-end ML initiatives, from design to production and operations. You will build scalable ML infrastructure, data pipelines, and feature libraries, and drive ML-driven solutions across engineering use cases.

You will collaborate with product, editorial, and engineering teams to translate business requirements into robust technical solutions, prioritize workstreams, and uphold CI/CD, observability, and

Qualifications

• Bachelor's degree in computer science, information systems, statistics, math, or equivalent.
• 8+ years of experience building and operating ML engineering systems in production environments.
• Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems.
• Comfortable operating at data collection, analysis, feature engineering, batch training, and online serving.
• Experience designing backend microservices for large-scale systems using REST.
• Experience with cloud infrastructure, preferably AWS.
• Experience with Spark, Databricks, Kinesis, and Kafka.
• Strong leadership, coaching, and mentoring skills.
• Excellent communication and collaboration in a fast-paced environment.

Responsibilities

• Own complex technical initiatives end-to-end, from design to production deployment and operations.
• Design and develop infra for ML lifecycle, data pipelines, and feature libraries.
• Drive ML-driven solutions for diverse engineering use cases (recs, object detection, tagging, RAGs).
• Partner with product, editorial, and engineering to translate business needs into robust tech solutions.
• Prioritize initiatives to deliver high-impact outcomes and mitigate risks.
• Champion best practices in code quality, testing, CI/CD, observability, and incident response.
• Mentor engineers and promote knowledge sharing across teams.

Skills

ML engineering

Data science

Deep learning

Statistical methods

Agile/Scrum

Leadership/mentoring

Communication

Education

Bachelor's degree in CS/IS/Math or equivalent

Tools

Databricks

Kinesis

Kafka

Datadog

Spark

AWS (Step Functions, Lambda, Glue, SQS, SNS)

Job description

The core responsibilities for the job include the following:

80% of the time:

• Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence.
• Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries.
• Drive data- and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, auto-generated tagging solutions, and RAGs.
• Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions.
• Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution.

20% of time:

• Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response.
• Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Contribute to technical documentation and promote knowledge sharing across teams.

Requirements:

• Minimum and Preferred. Included in Licenses/Certs (include functional experience as well as behavioral attributes and/or leadership capabilities).
• Bachelor's degree in computer science, information systems, statistics, math, or a comparable field of study, and/or equivalent work experience.
• 8+ years of experience building and operating ML engineering systems in production environments.
• Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems.
• Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving.
• Experience designing and developing backend microservices for large-scale distributed systems using REST.
• Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).
• Familiarity with developing and deploying Spark and ML pipelines.
• Hands-on experience with big data technologies such as Databricks, Kinesis, and Kafka.
• Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals.
• Experience with observability tools for metrics, logging, and monitoring such as Datadog.
• Experience working in Agile/Scrum development environments.
• Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment.