Staff Machine Learning Engineer Job at Uber (Bangalore)

Staff Machine Learning Engineer

The Marketplace Signals team at Uber is responsible for building and optimizing ...

Location

United States , San Francisco; Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D. or M.S. in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields
6+ years of industry experience in machine learning, including building and deploying ML models at scale
Experience in modern deep learning architectures and probabilistic modeling
Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
Solid understanding of MLOps practices, including design documentation, testing, and source code management with Git
Advanced skills in the development and deployment of large-scale ML models and optimization algorithms
Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.

Job Responsibility

Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts)
Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized
Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases
Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals
Ensure consistency and reliability across Uber's platform by maintaining high-quality marketplace signals that inform rider and driver experiences
Reduce technical debt by streamlining signal infrastructure and minimizing redundant computations
Work with real-time streaming data and large-scale distributed systems to ensure Uber's signals are up-to-date and responsive to market dynamics.

What we offer

Bonus program
Equity award
401(k) plan
Various benefits

Fulltime

Staff Machine Learning Engineer

Uber Marketplace is at the core of Uber's business, and Marketplace Matching is ...

Location

United States , San Francisco

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

PhD or equivalent in Computer Science, Engineering, Mathematics or related field
Programming language (e.g. C, C++, Java, Python, or Go)
5+ years of proven experience in the industry
Large-scale training using data structures and algorithms
Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib

Job Responsibility

Build elastic, scalable, and fault-tolerant distributed machine learning libraries and systems used to power machine learning development productivity across Uber
Work closely with engineers in the broader Uber ML/AI Platform Team (Michelangelo) to improve the broader ML Platform ecosystem for our users
Work closely with Uber's ML community (with ML Engineers, Data Scientists, and Researchers) to scope and build new abstractions for scalable machine learning

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Staff Machine Learning Engineer

Uber Marketplace is at the heart of Uber’s business, with Rider Pricing & Incent...

Location

United States , San Francisco; Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Masters degree in Computer Science, Engineering, Mathematics, or a related field, with 7+ years of full-time engineering experience
Proficiency in one or more programming languages (e.g., C, C++, Java, Python, Go)
Experience with machine learning and optimization algorithms

Job Responsibility

Lead a group of SWEs and MLEs working on rider pricing and promotions to develop and implement new machine learning and optimization techniques powering billions of rides around the world, and helping riders achieve their mobility needs
Improve the performance of models and algorithms powering pricing algorithms and promotion targeting
Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap
Mentor more junior team members by role modeling ML best practices
Collaborate with cross-functional teams to ensure alignment and drive Uber’s ridership and revenue growth
Help Uber’s end-users by making mobility options accessible and affordable

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Staff Machine Learning Engineer

The Consumer Incentives team is responsible for the profitability and growth tra...

Location

United States , New York; San Francisco; Sunnyvale

Salary:

232000.00 - 258000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Master (or equivalent in Computer Science, Engineering, Mathematics or related field) with 6+ years of full-time ML engineering experience
Expertise in deep learning and optimization algorithms
Experience with ML frameworks such as PyTorch and TensorFlow
Experience building and productionizing innovative end-to-end Machine Learning systems
Proficiency in one or more coding languages such as Python, Java, Go, or C++
Strong communication skills and can work effectively with cross-functional partners

Job Responsibility

Identifying strategic technical investments to push the efficiency frontier and boost business growth
Leading teams to design and implement ML/optimization solutions to meet ambitious business goals
Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation
Collaborating with cross-functional teams, including product, operations, and science partners

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Staff Machine Learning Engineer

Orbital uses AI to build data center hardware that outperforms the competition. ...

Location

United Kingdom , London

Salary:

Not provided

Orbital

Expiration Date

Until further notice

Requirements

5+ years of professional experience in ML/AI research or engineering
OR a relevant PhD + 2 years of professional experience in ML/AI research or engineering
Proven experience training, evaluating and productionising AI models at scale, with deep understanding of the full ML lifecycle from research to deployment
Strong engineering fundamentals with the ability to write high-quality, maintainable code and architect robust systems
A strong ability to reason about algorithms, system design, linear algebra, probabilistic concepts and ML engineering trade-offs
An ability to debug complex machine learning systems through meticulous attention to detail, testing of edge cases and carefully selected ablations
A genuine interest in building AI systems that enable breakthrough scientific and industrial applications

Job Responsibility

Set the technical bar and ensure engineering excellence
Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices through hands-on coding and technical review
Design robust, well-engineered systems that others can build upon, balancing research velocity with production requirements
Drive technical decisions on model selection, training approaches and deployment strategies
Deliver high-impact AI projects across diverse domains
Develop and deploy AI solutions across the entire technology development pipeline- computational chemistry simulations, agentic workflows and beyond
Rapidly upskill in new technical areas through close collaboration with domain experts
Demonstrate strong implementation skills through hands-on development, contributing significantly to the codebase
Balance research rigour with pragmatic engineering to deliver production-ready systems at scale
Push the frontier of ML research

Fulltime

Staff Machine Learning Engineer

Playlab seeks a Staff Machine Learning Engineer to join our growing Engineering ...

Location

Salary:

190000.00 - 250000.00 USD / Year

Playlab

Expiration Date

Until further notice

Requirements

7+ years building and deploying ML systems in production, with recent experience in generative AI and LLMs
Strong understanding of ML fundamentals, model fine-tuning, and evaluation methodologies
Experience building production AI systems - you understand latency, cost optimization, and evaluation challenges
Proficient in Python and ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.)
Thrive in high-agency, high collaboration cultures
Great communication that makes working remote-first work

Job Responsibility

Research, prototype, and implement ML systems that enable educators to build safe, effective AI applications - working with both LLMs and traditional ML models as appropriate
Stay on top of emerging AI research and technologies - evaluate what's relevant for education and integrate what works
Work cross-functionally with engineering, product, and educators to ensure ML systems solve real educational needs
Balance experimentation with production excellence - explore cutting-edge techniques while ensuring reliability, performance, and cost-effectiveness at scale
Contribute to our open-source ML infrastructure and help establish evaluation standards for educational AI
Mentor engineers on ML systems design and implementation through pairing and reviews

Fulltime

Staff Machine Learning Engineer

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and...

Location

United States , San Francisco; St. Louis; New York; Washington

Salary:

260400.00 - 362250.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

8+ years of experience building and deploying applied ML systems in production environments
Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps
Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation
Hands-on experience with retrieval systems, embeddings, or representation learning
Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end
Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 0→1 initiatives to production
Experience making thoughtful tradeoffs across performance, cost, reliability, and development velocity
This role will require an active security clearance or the ability to obtain a security clearance

Job Responsibility

Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability
Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data
Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently
Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets
Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions
Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts
Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments
Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams
Serve as a technical mentor and multiplier—raising the bar for system design, ML rigor, and production readiness across the organization

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity grant
commuter stipend

Fulltime

Staff Machine Learning Engineer

Tonal is looking for a Staff Machine Learning Engineer to help expand Tonal’s in...

Location

United States , San Francisco; Toronto

Salary:

200000.00 - 235000.00 USD / Year

Tonal

Expiration Date

Until further notice

Requirements

7 plus years of experience in software engineering or applied ML
5 plus with a Master’s degree
PhD with 3 plus years of experience
Strong coding skills in Python
Experience with frameworks such as PyTorch, TensorFlow, or JAX
Experienced in ML training, evaluation, and deployment workflows such as Sagemaker, MLFlow, Databricks, or similar
Deep understanding of time series modeling, human motion, or sensor based learning from devices such as force transducers, position encoders, IMUs, or cameras
Familiar with MLOps best practices and scalable model training pipelines
Strong communicator who can collaborate with scientists, product managers, and engineers
Track record of delivering performant ML systems from prototype to production

Job Responsibility

Design, implement, and optimize machine learning training pipelines and model serving infrastructure for real time applications
Develop algorithms and ML models that enable personalized training, adaptive coaching, and performance prediction
Fine tune and evaluate transformer based or self supervised learning models using Tonal’s multimodal dataset
Build data driven systems that measure training effectiveness, effort, and progression beyond traditional weight based metrics
Prototype, train, and deploy ML models that run efficiently at scale or on device
Collaborate cross functionally with Exercise Science, Product, and Software teams to deliver intelligent features that improve the member experience
Contribute to the development of automated tools for experimentation, model validation, and continuous retraining
Write high quality, maintainable Python code and work closely with backend engineers to integrate models into Tonal’s production systems
Mentor teammates and help shape Tonal’s growing AI and ML best practices

What we offer

Offers Equity
Health insurance
Retirement savings benefits
Life insurance
Disability benefits
Flexible paid time off
Parental leave
Other additional benefits (location dependent)

Fulltime

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Staff Machine Learning Engineer

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