# Senior Staff Machine Learning Engineer at Netradyne

> India · Staff · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Anetradyne%3A4739224005 (read 2026-11-06).

## Facts (observed)

- Company: [Netradyne](https://alderhq.app/companies/netradyne)
- Location text: Bengaluru, Karnataka, India; Office - Bengaluru
- Where it can be done from (inferred): India (evidence: "Location lists "bengaluru"")
- Posted: 2026-09-30 (37 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://www.netradyne.com/company/careers?gh_jid=4739224005
- Skills listed (inferred): Python, Java, Rust, C++, AWS, SQL, LLMs, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (India, n 6): p25 ₹33.4L, median ₹38.8L, p75 ₹43.7L
- H-1B filings at this company for similar roles, FY26: 2 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.

Job Responsibilities:

As a Senior Staff Machine Learning Engineer, you will set technical direction to our cross-functional team consisting of Data Scientists and Data/SW/ML Engineers. Your primary responsibilities will include:

• Owning the architecture of large-scale cloud ML systems end to end — data ingestion and feature pipelines, training infrastructure, model serving, monitoring and retraining.

• Design, develop and deploy production ready scalable cloud solutions that utilize Gen-AI, agentic AI, DNN, Traditional ML models, data-driven rules and ETL pipelines.

• Architecting distributed, fault-tolerant services and data platforms that operate reliably at high throughput, with clear SLAs, observability and cost controls.

• Applying advanced statistical methods, machine learning and deep learning techniques to uncover trends, patterns, and anomalies in large-scale datasets.

• Creating robust frameworks and tools to automate and enhance data mining, labeling, model training, and validation processes for internal ML/DL initiatives.

• Setting engineering standards across teams — design review, testing strategy, CI/CD and release practice — and mentoring Staff and Senior engineers.

• Collaborating closely with cross-functional teams to identify and implement data-driven solutions addressing key business challenges.

• Conducting studies, setting up automation tools and frameworks, and regularly publishing internal and external KPI audits.

• Develop and maintain ROI models and frameworks to quantify the business impact of data science initiatives.

Requirements:

• B. Tech, M. Tech or PhD in Data Science, Computer Science, Electrical Engineering, Operations Research, Statistics, Mathematics or a related area.

• At least 8 years of working experience in machine learning, data science or a related domain, including 5+ years building and shipping production ML systems at scale.

• Demonstrated depth on both sides of the role: building distributed data and ETL pipelines, and training, tuning and deploying models in production.

• Strong large-scale software engineering fundamentals: distributed systems, concurrency, microservice and API design, caching, queueing, idempotency and failure handling.

• Proven experience designing and operating systems on public cloud at scale — AWS preferred (Kinesis, SQS, EKS, Lambda, Auto Scaling Groups, S3), including cost, capacity and reliability trade-offs.

• Strong foundational knowledge in Statistics, Probability Theory, Machine Learning and Gen-AI.

• Excellent programming skills – Python (required) and Java/Rust/C++ (desired), with strong fundamentals in object-oriented programming, algorithms, and data structures.

• Good understanding of database internals and schema design for relational (RDBMS) and non-relational (NoSQL) data stores, including the ability to write and reason about complex SQL.

• Experience with transformer architectures and large language models (LLMs), and with Gen-AI tools and workflows.

• Knowledge of best practices in software development, including version control, code review, automated testing, continuous integration and continuous delivery.

• Experience with observability and production operations — metrics, tracing, logging, alerting and incident response for services and ML pipelines.

• Proven ability to influence technical decisions beyond one's own team.

Desired skills:

• Agentic AI systems — tool use, planning, multi-agent orchestration, memory, guardrails and agent evaluation.

• Hands-on experience with the Claude Agent SDK, OpenAI Agents SDK and Model Context Protocol (MCP) servers and connectors.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Anetradyne%3A4739224005 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.