Machine Learning Manager - Applied ML Job at Cohere (New York)

Manager- Applied Sciences / Machine Learning

The Microsoft Content Product team is seeking a Manager-Applied Sciences/Machine...

Location

United States , Redmond

Salary:

163000.00 - 296400.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience
OR equivalent experience
3+ years of people management experience

Job Responsibility

Lead and grow a team of Applied Scientists and Machine Learning Engineers, including hiring, coaching, and developing talent across Applied Science and engineering
Define technical vision and strategy for recommendation systems, Artificial Intelligence Generated Content (AIGC), and LLM-powered content generation
Drive end-to-end execution across multiple initiatives, from ideation and design to production and iteration
Oversee system architecture and scalability, ensuring robust, efficient, and high-quality ML solutions in production
Partner cross-functionally with product, engineering, and leadership teams to align on priorities and deliver customer impact
Champion innovation in AIGC applications, ranking, and recommendation algorithms
Mentor and elevate the team, fostering a culture of technical excellence, collaboration, and continuous learning
Communicate progress, insights, and strategy to senior leadership and stakeholders

Fulltime

Director, Applied Machine Learning

This leader works in tight partnership with the MLOps team (deployment, monitori...

Location

India , Bangalore

Salary:

Not provided

Danaher Corporation

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, engineering, data science, or a related field
advanced degree preferred
10+ years of experience in applied machine learning and/or data science, with 4+ years in people leadership roles
Proven experience building and scaling teams that deliver machine learning models into production with measurable impact
Strong applied foundation in ML methods and evaluation, with the judgment to select practical approaches and manage tradeoffs
Demonstrated ability to partner effectively with MLOps and platform teams to operationalize models reliably and securely
Experience working in a product delivery model, collaborating with product managers, engineers, and business stakeholders in a matrixed environment
Strong communication skills, including the ability to explain technical tradeoffs, align on priorities, and influence senior stakeholders
Working knowledge of cloud-based data and ML stacks and modern engineering practices (CI/CD, testing, observability, security by design)
Delivering ML solutions in regulated environments (e.g., life sciences, healthcare, biotech), including familiarity with SOX and/or GxP expectations

Job Responsibility

Build and lead a new applied machine learning team, including hiring, coaching, career development, and setting a high-performance culture with clear delivery accountability
Establish the applied ML charter, operating model, and engagement pattern with data product teams to ensure ML work is prioritized by value and delivered as part of product roadmaps
Own model development end-to-end, including problem framing, feature strategy, model selection, training, evaluation, and iteration based on business and technical metrics
Partner with data product managers and domain stakeholders to define use cases, success measures, and adoption plans, ensuring solutions are usable and drive outcomes
Work closely with the MLOps team to productionize models with strong engineering rigor, including CI/CD, model registries, reproducible training, automated testing, monitoring, and retraining triggers
Collaborate with the data platform team to ensure ML solutions leverage trusted, standardized data assets and patterns (e.g., curated datasets, lineage, access controls, scalable pipelines)
Define and enforce best practices for applied ML delivery, including experimentation discipline, documentation, model governance, and responsible AI practices appropriate for the business context
Ensure models and workflows meet security, privacy, and compliance requirements, including operating effectively in SOX and GxP environments where applicable
Drive reuse and scale by developing shared components (feature patterns, evaluation templates, reference architectures) and reducing one-off model implementations
Provide senior technical leadership and pragmatic guidance to stakeholders on when ML is appropriate versus rules-based or analytical alternatives

Fulltime

Senior Engineering Manager - Machine Learning

As Sr Engineering Manager for the Shopping ML team, you will join a team dedicat...

Location

United States , Sunnyvale; San Francisco; New York

Salary:

267000.00 - 297000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

MS or equivalent experience in Computer Science, Engineering, Mathematics, or related field
10+ years of industry experience in software engineering and AI/ML
5+ years of experience directly managing engineering or ML teams, with a track record of hiring, mentoring, and growing high-performance teams
Deep understanding of machine learning fundamentals, with practical experience applying them to real-world problems.
Experience working with cross-functional teams (product, science, product ops, etc.)

Job Responsibility

Define and execute the Shopping ML product and engineering roadmap and strategy, focusing on personalization and discovery experiences that enhance multiple surfaces on the Uber Eats app including the store, checkout, and s experiences.
Collaborate with product managers, data scientists, designers, and operations to identify opportunities, prioritize initiatives, and deliver ML-powered features that feel intuitive and assistive.
Develop scalable systems that help consumers easily discover and order food and groceries, while also surfacing personalized recommendations for future meals or unmet needs.
Partner with other product & engineering teams to ensure ML frameworks and capabilities are leveraged to create cohesive, delightful user experiences.
Stay on top of industry trends and emerging best practices in machine learning and personalization to ensure Uber Eats continues to lead in innovation.

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

Manager, Machine Learning on Orbit

Boston Dynamics is building the world’s most advanced robots. The Spot quadruped...

Location

United States , Waltham

Salary:

187580.00 - 275117.00 USD / Year

Boston Dynamics

Expiration Date

Until further notice

Requirements

BS and 10+ years of experience, or MS and 7+ years of industry experience in Computer Science, Machine Learning, Robotics, or a related field
Expert-level software development skills, particularly in python, with a strong command of software architecture, design patterns, and performance optimization techniques
Experience training, fine tuning, and applying state of the art generative ai models. Preferably focused on computer vision tasks
Experience with common ML tools (CUDA, pytorch), architectures and workflows
Ability to track the current state of the art, and identify opportunities for product applications
A willingness to dive deep into challenging problems in computer vision, develop creative customer-focused solutions in collaboration with teammates, and clearly communicate findings

Job Responsibility

Be a lead on a team of ~5 machine learning engineers
Research, prototype, and deploy models leveraging multimodal data from robotic sensors to extract useful site information - anomalous machine states, object classification, etc
Establish effective methods of evaluating inspection model performance
Curate datasets to be used in model training, fine-tuning and evaluation
Identify and employ model performance improvement strategies - e.g. fine tuning, model selection, and prompt engineering

What we offer

medical, dental vision, 401(k), paid time off and an annual bonus structure

Fulltime

Senior Applied Machine Learning Engineer - Asset Intelligence

We are seeking a highly skilled and motivated Senior Applied Machine Learning En...

Location

United States , San Francisco

Salary:

Not provided

MaintainX

Expiration Date

Until further notice

Requirements

7+ years of experience in Machine Learning, Data Science, or Applied AI
Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar)
Proven experience deploying production ML systems at scale
Strong background in LLMs, time-series modeling, and anomaly detection for real-world data
Demonstrated ability to lead architectural decisions, mentor engineers, and collaborate across product, data, and platform teams
Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker)
Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred

Job Responsibility

Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products
Architect end-to-end ML systems—from data ingestion and feature engineering to model training, deployment, and monitoring
Mentor a growing team of ML and data engineers, instilling best practices for experimentation, evaluation, and model lifecycle management
Partner with product and engineering leaders to align AI roadmap with customer needs and business goals
Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining
Drive performance optimization through techniques like quantization, distillation, and scalable inference serving
Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence
Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security

What we offer

Competitive salary and meaningful equity opportunities
Healthcare, dental, and vision coverage
401(k) / RRSP enrollment program
Take what you need PTO
A high impact Culture: You’ll work with Smart, Humble Optimists across the globe
Meritocratic environment where ideas and outcomes are publicly celebrated

Fulltime

Senior Applied Machine Learning Engineer - Asset Intelligence

We are seeking a highly skilled and motivated Senior Applied Machine Learning En...

Location

Canada , Montreal, Toronto, Vancouver

Salary:

Not provided

MaintainX

Expiration Date

Until further notice

Requirements

7+ years of experience in Machine Learning, Data Science, or Applied AI
Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar)
Proven experience deploying production ML systems at scale
Strong background in LLMs, time-series modeling, and anomaly detection for real-world data
Demonstrated ability to lead architectural decisions, mentor engineers, and collaborate across product, data, and platform teams
Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker)
Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred

Job Responsibility

Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products
Architect end-to-end ML systems—from data ingestion and feature engineering to model training, deployment, and monitoring
Mentor a growing team of ML and data engineers, instilling best practices for experimentation, evaluation, and model lifecycle management
Partner with product and engineering leaders to align AI roadmap with customer needs and business goals
Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining
Drive performance optimization through techniques like quantization, distillation, and scalable inference serving
Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence
Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security

What we offer

Competitive salary and meaningful equity opportunities
Healthcare, dental, and vision coverage
401(k) / RRSP enrollment program
Take what you need PTO

Engineering Manager, Machine Learning

Dandy is transforming the massive and antiquated dental industry—an industry wor...

Location

United States

Salary:

216750.00 - 255000.00 USD / Year

Dandy

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related field with a strong focus on computer vision or machine learning
Extensive experience in SOTA 2D deep learning and/or experience with 3D deep learning
6+ years (or 5 years + PhD) of industry experience in applied machine learning
At least 1 year in a leadership or management role
Strong people management skills with a track record of team development, mentorship, and retention
Demonstrated ability to lead cross-functional efforts across product, engineering, research, and operations
Strong coding skills in Python
Experience with ML frameworks like PyTorch

Job Responsibility

Lead execution of the ML roadmap, managing a team focused on 3D deep learning and computer vision
Partner with product, engineering, and research stakeholders to align and execute technical strategy with business goals
Lead and grow a high-performing team of ML scientists, engineers, and researchers
Drive the development of computer vision models to extract structure from unstructured, information-dense 3D scans
Research and implement state-of-the-art methods for developing models to accomplish 3D generative AI tasks as well as conventional computer vision tasks
Collaborate with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
Manage large-scale datasets to develop both generic models as well as fine-tune models for specific applications
Develop evaluation methods to establish confidence in our datasets and models
Implement best practices for our MLOps pipelines, ensuring robust and scalable deployment of models

What we offer

Offers Equity
Healthcare
Dental
Mental health support
Parental planning resources
Retirement savings options
Generous paid time off

Fulltime

Applied ML Manager

We’re looking for an ML Manager to lead our ML team (currently 4 people across v...

Location

United States , San Francisco

Salary:

250000.00 - 300000.00 USD / Year

Speak

Expiration Date

Until further notice

Requirements

8–10+ years overall experience in applied ML, with a track record of shipping ML and LLM systems into production
4+ years people management experience, including leading 1:1s, giving feedback, and handling performance
Strong technical judgment in applied ML (not primarily ML infra/MLOps), including ability to define and run rigorous evaluations
Excellent metric sense and analytical thinking: can translate ambiguous goals into measurable outcomes and make tradeoffs
Strong cross-functional collaboration skills with Product, Engineering, and Design
Clear written communication: can write crisp strategy docs, decision memos, and goal docs

Job Responsibility

Manage and grow the ML team through clear expectations, regular feedback, and strong coaching
Define quarterly ML goals and success metrics, establish baselines, and build a visible “scoreboard” for progress
Drive end-to-end execution on key ML initiatives: planning, evaluation, iteration, rollout, and impact measurement
Build a repeatable model evaluation and experimentation process (quality, performance, reliability), including rollout criteria
Partner with Product and Engineering leaders to align roadmaps, clarify ownership, and ensure ML work is shippable and predictable
Identify gaps in our current ML strategy, propose concrete bets, and translate direction into actionable plans
Help hire thoughtfully as the team grows, without prematurely scaling into a large org

What we offer

Offers Equity
Join a fantastic, tight-knit team at the right time
Do your life's work with people you’ll love working with
Global in nature: live in over 40 countries, dedicated offices in San Francisco, Ljubljana, Seoul, and Tokyo, opportunity to talk to users and travel
Impact people's lives in a major way

Fulltime

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Machine Learning Manager - Applied ML

Job Description

Job Responsibility

Requirements

What we offer

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