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applied ai ml manager of software engineering

JPMorganChase

<div>JOB DESCRIPTION 
This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.<div>
As a Manager of AI/ML Engineering team at JPMorgan Chase within the Business Banking , you lead our dynamic teams and will be responsible for applying advanced machine learning techniques to intricate task such as natural language processing, document screening and manage day-to-day implementation activities by identifying and escalating issues
Job responsibilities<ul><li>
Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, or recommendation systems</li><li>
Choosing, extending, and innovating ML strategies for various banking problems</li><li>
Provides guidance to immediate team of software engineers on daily tasks and activities</li><li>
Sets the overall guidance and expectations for team output, practices, and collaboration</li><li>
Anticipates dependencies with other teams to deliver products and applications in line with business requirements</li><li>
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production</li><li>
Learning about and understanding our supported businesses in order to drive practical and successful solutions</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification in Software Engineering concepts and 5+ years applied experience and hand-on industry experience in Machine Learning.</li><li>
Good understanding of the latest advancement of NLP concepts, such as the transformer architecture and knowledge distillation.</li><li>
Experience in classical ML techniques including classification, clustering, optimization, cross validation, data wrangling, feature selection, and feature extraction</li><li>
Experience leading technology projects</li><li>
Experience managing technologists</li><li>
Proficient in automation and continuous delivery methods</li><li>
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments</li><li>
Solid written and spoken communication skills</li><li>
Proficient in all aspects of the Software Development Life Cycle</li><li>
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security</li><li>
Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines</li></ul>
Preferred qualifications, capabilities, and skills<ul><li>
Hands-on experience with virtual assistant model development and optimization</li><li>
Familiarity with continuous integration models and unit test development</li><li>
Experience with A/B experimentation and data/metric-driven product development</li></ul>
</div>ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
 
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div>

Applied AI/ML Manager of Software Engineering

Catalyst Labs

<div>
 
 About The Job ML Engineer
 
 
 
 
 Our Client
 
 
 
 Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.
 
 
 By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
 
 
 
 About Us
 
 
 
 Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that&rsquo;s deeply embedded in our clients&rsquo; recruitment operations.
 
 
 We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.
 
 
 
 Location
 
 : New York, NY
 
 
 
 Work type
 
 : Full Time,
 
 
 
 Compensation
 
 : above market base + bonus + equity
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 </li>
 <li>
 Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 </li>
 <li>
 Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 </li>
 <li>
 Build agents capable of operating natively on real-world audio inputs.
 </li>
 <li>
 Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 </li>
 <li>
 Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 </li>
 <li>
 Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 </li>
 <li>
 Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
 </li>
 <li>
 1-6 years of professional experience in ML engineering.
 </li>
 <li>
 Strong programming skills in Python (TypeScript experience is a plus).
 </li>
 <li>
 Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Familiarity with cloud environments and infrastructure (preferably AWS).
 </li>
 <li>
 Strong understanding of data pipeline design, real-time inference, and model monitoring.
 </li>
 <li>
 Excellent communication skills with the ability to engage directly with customers and stakeholders.
 
 
 </li>
 </ul>
 
 Core Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying ML models into production environments.
 </li>
 <li>
 Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 </li>
 <li>
 Experience with audio-focused ML projects or similar domains involving unstructured data.
 </li>
 <li>
 Proficiency in building scalable data pipelines for model training and evaluation.
 </li>
 <li>
 Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 </li>
 <li>
 Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
 </li>
 </ul>
</div>

ML Engineer

<div>JOB DESCRIPTION 
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team
As a Software Engineer III (Machine Learning Platform Engineer) at JPMorgan Chase within the Consumer &amp; Community Banking (CCB) line of business, you serve as a seasoned member of an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver trusted, market-leading infrastructure and tools that empower data scientists and ML engineers to develop, deploy, and monitor models efficiently and securely. You are responsible for implementing critical technology solutions across multiple technical areas to support the firm&rsquo;s business objectives and drive innovation in ML platform capabilities.
Job responsibilities<ul><li>
Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.</li><li>
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.</li><li>
Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.</li><li>
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.</li><li>
Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.</li><li>
Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.</li><li>
Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.</li><li>
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.</li><li>
Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies.</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on software engineering concepts and 3+ years applied experience</li><li>
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure</li><li>
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
</li><li>Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
</li><li>Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure</li><li>
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring</li><li>
Experience developing APIs and platform services for ML workflows
</li><li>Solid knowledge of the software development life cycle and agile methodologies
</li><li>Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives
</li></ul>Preferred qualifications, capabilities, and skills<ul><li>
Familiarity with Databricks for scalable data engineering and ML platform integration</li><li>
Experience working with Snowflake for cloud-based data warehousing and analytics</li><li>
Exposure to Snorkel AI for programmatic data labeling and training data management</li><li>
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)</li><li>
Familiarity with feature stores, model registries, and ML metadata management</li><li>
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)</li><li>
Experience with RESTful APIs and microservices architectures</li></ul>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div> 
 
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Software Engineer III - Machine Learning Platform

Google

<div>This posting is for an existing vacancy. 
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Waterloo, ON, Canada; Toronto, ON, Canada; New York, NY, USA.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>8 years of experience in software development. 
</li>
<li>5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.</li>
<li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 
</li>
<li>5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation).</li>
<li>Experience with core GenAI concepts (e.g., LLM, Multi-Modal) and with text, image, or audio generation.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>8 years of experience with data structures and algorithms.</li>
<li>3 years of experience in a technical leadership role leading project teams and setting technical direction.</li>
<li>Experience in prompt development, model evaluation, and the creative application of Artificial Intelligence (AI).</li>
<li>Experience in Vertex AI, BigQuery, Cloud Storage, Dialogflow.</li>
<li>Ability to be flexible and resilient in dynamic environments and take ownership of urgent business or customer issues.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As a Forward Deployed Developer (FDE), you will be at the forefront of applying Google's Generative AI to solve real-world issues for our customers. You will act as a specialized software developer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents on our Customer Engagement Suite (CES) platform. You will bridge the gap between our core product developing teams and customer needs, directly accelerating customer success and shaping the future of our AI products.
Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous. 
 
For United States Applicants: 
 
The US base salary range for this full-time position is $262,000-$365,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. 
 
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. 
 
For Canada Applicants:
The Canada base salary range for this full-time position is CAD 260,000-267,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Please note that the compensation details listed in Canada role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Partner directly with customers to understand their business issues. Design, co-develop, debug, and deploy custom conversational AI agents and solutions to accelerate their time to value.</li>
<li>Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and even contribute directly to the core product codebase to resolve critical customer issues. 
</li>
<li>Systematize your learnings from customer engagements by creating reusable tools, building documentation and accelerators, and establishing best practices that can be used across the organization. 
</li>
<li>Serve as a critical feedback loop to our core product and developing teams. Synthesize firsthand insights from the field to influence product strategy, identify feature gaps. 
</li>
<li>Act as a subject matter expert, providing technical guidance and best practices to customers on agent improvement, performance tuning, Continuous Integration/Continuous Deployment (CI/CD) pipelines, and production readiness. 
</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Staff Forward Deployed Developer, Google Cloud

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. 
 
We are seeking an experienced Data Scientist to join the Sponsored Products Auction team. This team is responsible for building and evaluating mechanisms to rank and price billions of ad impressions per day. We're looking for a Data Scientist to define measures of auction efficiency and produce insights into the quality of inputs to our auction (supply, demand, ML model predictions). This role will also be responsible for exploratory data analysis to identify opportunities for improvement of the system and working closely with Economists, Applied Scientists and Engineers to improve our product. 
 
As a Data Scientist on this team, you will: 
<ul><li>Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.</li><li>Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
</li><li>Apply statistical and machine learning knowledge to specific business problems and data.</li><li>Build decision-making models and propose solution for the business problem you define.</li><li>Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.</li><li>Analyze historical data to identify trends and support optimal decision making.</li><li>Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.</li><li>Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.</li><li>Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.</li></ul> 
Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon&rsquo;s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. 
 
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. 
 
Team video https://youtu.be/zD_6Lzw8raE</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>2+ years of data scientist experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Bachelor's degree</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in Python, Perl, or another scripting language</li><li>Experience in a ML or data scientist role with a large technology company</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, SEATTLE - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 
 
 Lyft Ads is one of Lyft&rsquo;s newest and fastest-growing businesses, focused on building the world&rsquo;s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey&mdash;before, during, and after a ride&mdash;by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.
 
 
 We are seeking an
 
 Algorithms Scientist
 
 to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You&rsquo;ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.
 
 
 This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands-on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders&mdash;pushing the boundaries of personalization, measurement, and real-time optimization in a dynamic marketplace.
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and deploy production-grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
 </li>
 <li>
 Own the end-to-end lifecycle of modeling projects &mdash; including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
 </li>
 <li>
 Collaborate closely with Ads Engineering to integrate models into real-time ad-serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
 </li>
 <li>
 Analyze large-scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
 </li>
 <li>
 Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system-level outcomes.
 </li>
 <li>
 Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long-term maintainability.
 </li>
 <li>
 Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
 </li>
 <li>
 Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
 </li>
 <li>
 Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement &mdash; and proactively identifying opportunities to apply them.
 </li>
 <li>
 Contribute to Lyft Ads&rsquo; modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.
 
 
 </li>
 </ul>
 Experience:
 
 
 <ul>
 <li>
 Master&rsquo;s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
 </li>
 <li>
 3&ndash;5 years of hands-on ML/applied science experience, ideally involving production models, large-scale systems, or ads/recommendation/relevance domains. Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn; ability to write clean, efficient, production-adjacent code.
 </li>
 <li>
 Experience working with large-scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
 </li>
 <li>
 Practical experience building and evaluating:
 </li>
 <ul>
 <li>
 Ranking and relevance models
 </li>
 <li>
 Optimization or pacing algorithms
 </li>
 <li>
 Predictive models for CTR, CVR, or user response
 </li>
 <li>
 Causal or experimentation-based measurement methods
 </li>
 </ul>
 <li>
 Understanding of online/offline evaluation techniques, including:
 </li>
 <ul>
 <li>
 Offline metrics (AUC, NDCG, MRR, calibration)
 </li>
 <li>
 A/B testing methodologies
 </li>
 <li>
 Bias correction and counterfactual estimation
 </li>
 </ul>
 <li>
 Ability to solve ambiguous problems by structuring analyses, evaluating trade-offs, and proposing algorithmic solutions grounded in scientific rigor.
 </li>
 <li>
 Strong communication skills, with an ability to clearly explain model behavior, constraints, trade-offs, and recommendations to engineering, product, and sales partners.
 </li>
 <li>
 Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
 </li>
 <li>
 Curiosity, initiative, and a track record of delivering measurable improvements through high-quality modeling.
 
 
 </li>
 </ul>
 
 Benefits:
 
 
 
 <ul>
 <li>
 Great medical, dental, and vision insurance options with additional programs available when enrolled
 </li>
 <li>
 Mental health benefits
 </li>
 <li>
 Family building benefits
 </li>
 <li>
 Child care and pet benefits
 </li>
 <li>
 401(k) plan to help save for your future
 </li>
 <li>
 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
 </li>
 <li>
 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
 </li>
 <li>
 Subsidized commuter benefits
 </li>
 <li>
 Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
 
 
 </li>
 </ul>
 Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
 
 
 Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
 
 
 The expected base pay range for this position in the New York City area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
 
 
 Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
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