Manager- Applied Sciences / Machine Learning Job at Microsoft Corporation (Redmond)

Machine Learning Manager - Applied ML

We are looking for a Machine Learning Manager to lead our East Coast Applied ML ...

Location

United States , New York

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Machine Learning, or a related field (Master’s or PhD preferred)
8+ years in AI/ML, including several years in technical leadership roles
Proven success leading large ML teams and delivering complex AI solutions at scale
Experience with enterprise deployments, including custom model development and fine-tuning
Deep understanding of LLMs, their training, deployment, and real-world constraints
Hands-on experience with RAG pipelines, agentic systems, and multi-modal applications
Proficiency in ML frameworks such as PyTorch or TensorFlow
Familiarity with modern cloud platforms (AWS, GCP, Azure) and ML infrastructure best practices
Strong ability to translate business requirements into scalable ML solutions
Track record of product thinking and technical decision-making aligned with customer needs

Job Responsibility

Define and drive the long-term vision for the Applied ML team in alignment with Cohere’s product and business goals
Shape the roadmap for custom model development, fine-tuning, and advanced implementations that address nuanced enterprise challenges
Collaborate closely with executive leadership to prioritize high-impact initiatives and strategic customer engagements
Lead and grow a high-performing team of ML engineers through hiring, coaching, and mentorship
Foster a culture of ownership, innovation, and continuous learning
Establish and evolve team processes to maximize productivity and execution speed
Partner with Product to define and deliver novel, scalable ML solutions that differentiate Cohere in the market
Guide the development of reusable frameworks and abstractions that streamline deployment across customer use cases
Oversee performance optimization and evaluation of models in real-world enterprise environments
Act as a trusted technical advisor to strategic customers—translating needs into actionable plans

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

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

Engineering Manager, Machine Learning Platform

Dandy is transforming the massive and antiquated dental industry. We are establi...

Location

United States

Salary:

216750.00 - 255000.00 USD / Year

Dandy

Expiration Date

Until further notice

Requirements

Bachelor’s in Computer Science, Electrical Engineering, Robotics, or a related field
5+ years of industry experience in applied machine learning
at least 2+ years in a leadership or management role
Deep understanding of ML Platform best practices: CI/CD for ML, model deployment, observability, and lifecycle management
Strong people management skills with a track record of team development, hiring mentorship, and retention
Strong Python skills and experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
Hands-on experience with model optimization, hyperparameter tuning, evaluation, monitoring, and benchmarking
Familiarity with Docker, Kubernetes, Kubeflow, and cloud platforms (AWS, GCP, or Azure)
preference for GCP tools (Vertex AI, BigQuery, Dataflow, GKE)
Demonstrated ability to lead cross-functional efforts across product, engineering, research, and operations.

Job Responsibility

Lead execution of the ML roadmap, with a focus on building scalable, production-grade ML Platform infrastructure for 3D deep learning and computer vision applications
Build and lead a high-performing ML Platform team, with an emphasis on reliability, reproducibility, and efficient model lifecycle management
Partner with product, engineering, and research stakeholders to translate ML innovations into robust, deployable systems that support key business objectives
Oversee the end-to-end deployment of computer vision models that extract structure from complex 3D scan data, ensuring production readiness and performance at scale
Drive experimentation and implementation of SOTA techniques for 3D generative AI, while ensuring they are integrated into robust ML Platform workflows
Collaborate cross-functionally to identify pain points and bottlenecks in current ML pipelines and deliver improvements through automation and tooling
Manage large-scale data pipelines, versioning, and labeling workflows to support both generalized and fine-tuned model development
Define and implement rigorous evaluation and monitoring strategies to maintain high model quality, mitigate drift, and ensure reliability in production
Establish and maintain best practices for CI/CD of ML models, including model versioning, rollback mechanisms, and monitoring for performance and integrity.

What we offer

Offers Equity
healthcare
dental
mental health support
parental planning resources
retirement savings options
generous paid time off

Fulltime

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Manager- Applied Sciences / Machine Learning

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