staff machine learning engineer

Ibotta

<div>Ibotta is seeking a Staff Machine Learning Engineer to join our Core Data &amp; Analytics team and contribute to our mission to Make Every Purchase Rewarding. We&rsquo;re looking for someone who has a passion for building scalable machine learning solutions using technologies and tools such as Python, Spark, Databricks, AWS, Sagemaker, etc. As a Staff Machine Learning Engineer, you will act as a technical leader and delivery owner for complex, high-impact ML initiatives spanning foundation models, data systems, and large-scale ML platforms. This role will immediately impact ML strategy and drive impact through the support, guidance, and collaboration with multiple teams as part of our analytics organization . We&rsquo;re looking for a technical leader to further mature our current infrastructure and abstractions and identify new opportunities to add value through ML applications.
This position is available in multiple locations:
Denver, Colorado - if you are in or willing to relocate to the Denver area, this is a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday).
Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NY, NC, OH, OK, PA, TN, TX, UT, VA, WA, WI. Not based in one of these areas? We will offer a relocation bonus to help make your move to the Mile High City a smooth one.
What you will be doing:
<ul><li>Lead the design, development, and deployment of production-grade ML systems across the organization.
</li><li>Work with Ibotta architecture and Machine Learning Platform teams to ensure integration of machine learning services and pipelines in larger technology infrastructure.
</li><li>Act as a liaison between technical teams and non-technical stakeholders to communicate complex concepts clearly.
</li><li>Communicate complex machine learning solutions, concepts and the results of analyses in a clear and effective manner to business stakeholders and technology leaders to maximize the effectiveness of machine learning initiatives.
</li><li>Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous experimentation, and best practices.
</li><li>Embrace and uphold Ibotta&rsquo;s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency &amp; A good idea can come from anywhere
</li></ul>What we are looking for:
<ul><li>6+ years of professional industry experience as a Machine Learning Engineer or Software Engineer, focused on deploying machine learning systems at scale.
</li><li>Advanced knowledge of multiple ML frameworks like: Sklearn, TensorFlow, Sagemaker, Spark ML.
</li><li>Expertise working with distributed big-data tools and event-based architectures, ideally Spark and Kafka.
</li><li>Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine learning models in high traffic applications.
</li><li>Experience working within a cloud-based infrastructure, ideally AWS.
</li><li>Track record of mentoring junior engineers or leading cross-functional initiatives.
</li></ul>About Ibotta (&quot;I bought a...&quot;)
Ibotta (NYSE: IBTA) is a leading performance marketing platform allowing brands to deliver digital promotions to over 200 million consumers through a network of publishers called the Ibotta Performance Network (IPN). The IPN allows marketers to influence what people buy, and where and how often they shop &ndash; all while paying only when their campaigns directly result in a sale. American shoppers have earned over $2.6 billion through the IPN since 2012. The largest tech IPO in history to come out of Colorado, Ibotta is headquartered in Denver, and is continually listed as a top place to work by The Denver Post and Inc. Magazine.
To learn more about what our Tech teams are doing day to day, visit Building Ibotta on Medium.com .
Additional Details:
<ul><li>This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Lifestyle Spending Account, Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, snacks, and occasional meals.
</li><li>Base compensation range: $206,000 - $230,000 Equity is included in overall compensation package. This compensation range is specific to the United States labor market and may be adjusted based on actual experience.
</li><li>Ibotta is an Equal Opportunity Employer. Ibotta&rsquo;s employment decisions are made without regard of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected status.
</li><li>Applicants must be currently authorized to work in the United States on a full-time basis.
</li><li>Applicants are accepted until the position is filled.
</li><li>For the security of our employees and the business, all employees are responsible for the secure handling of data in accordance with our security policies, identifying and reporting phishing attempts, as well as reporting security incidents to the proper channels.
</li></ul>Recruiting Agency Notice
 
Ibotta does not accept agency resumes and is not responsible for any fees related to unsolicited resumes. Please do not forward resumes to any Ibotta employees.
#LI-Remote
#BI-Remote
#BI-Hybrid</div>

Staff Machine Learning Engineer

Intuit

<div><h2 class="jobSectionHeader">Overview</h2><div>
Come join Intuit as a Staff Machine Learning Engineer!</div><div>
In this role, you&rsquo;ll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You&rsquo;ll be expected to help conceive, code, and deploy models at scale using the latest industry tools. Important skills include creating data pipelines, developing and deploying models, and machine learning operations.</div> 
Responsibilities<ul><li>
Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.</li><li>
Build &quot;machine learning ready&quot; feature pipelines.</li><li>
Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.</li><li>
Run regular A/B tests, gather data, and draw conclusions on the impact of your models.</li><li>
Monitor and maintain production models.</li><li>
Work cross functionally with product managers, AI scientists and product engineers, and communicate results to peers and leaders.</li><li>
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.</li></ul><div></div> 
Qualifications<ul><li>
BS, MS, or PhD degree in Computer Science or related field, or equivalent work experience.</li><li>
7+ years of experience</li><li>
Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).</li><li>
Knowledge of machine learning techniques (i.e. classification, regression, and clustering).</li><li>
Understand machine learning principles (training, validation, etc.)</li><li>
Knowledge of data query and data processing tools (i.e. SQL)</li><li>
Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning).</li><li>
Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.</li><li>
Experience deploying highly scalable software supporting millions or more users</li><li>
Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP)</li><li>
Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users</li></ul> 
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at [1] Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: Bay Area California $ 202,500- 274,000 References Visible links 1. https://www.intuit.com/careers/benefits/full-time-employees/ Mountain View $202500 - $274000 
Plano, TX $178500- $241500</div>

GEICO

<div>At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers&rsquo; expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here. That&rsquo;s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers
GEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization&mdash;designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes. 
You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologies
About the role<ul><li>
Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.</li><li>
Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.</li><li>
GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.</li></ul>
What you&rsquo;ll do<ul><li>
Own ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.</li><li>
Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.</li><li>
Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).</li><li>
Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact.</li><li>
Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.</li><li>
Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems.</li><li>
Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.</li><li>
Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence.</li><li>
Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.</li><li>
Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices.</li><li>
Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards.</li><li>
Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.</li></ul>
Minimum qualifications<ul><li>
Bachelor&rsquo;s degree or above in Computer Science, Engineering, Statistics, or related field.</li><li>
10+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#).</li><li>
10+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components:<ul><li>
Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval)</li><li>
Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg</li><li>
Streaming: Kafka; plus Flink/Spark Streaming experience</li><li>
Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra)</li><li>
Distributed compute: Spark, Ray</li><li>
Workflow orchestration: Airflow, Temporal</li></ul></li><li>
6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.</li><li>
6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.</li></ul>
Preferred qualifications (GenAI as a plus)<ul><li>
Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling.</li><li>
Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks.</li><li>
Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.</li><li>
Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices.</li><li>
Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.</li><li>
Experience with high-throughput, low-latency inference and real-time feature pipelines.</li></ul>
#LI-JK1 
Annual Salary
$150,000.00 - $300,000.00
The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate&rsquo;s work experience, education and training, the work location as well as market and business considerations. 

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position. 
The GEICO Pledge:
Great Company: At GEICO, we help our customers through life&rsquo;s twists and turns. Our mission is to protect people when they need it most and we&rsquo;re constantly evolving to stay ahead of their needs.
We&rsquo;re an iconic brand that thrives on innovation, exceeding our customers&rsquo; expectations and enabling our collective success. From day one, you&rsquo;ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people&rsquo;s lives.
Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career &ndash; and your potential &ndash; in mind. You&rsquo;ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.
Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.<ul><li>
Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family&rsquo;s overall well-being.</li><li>
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.</li><li>
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.</li><li>
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.</li></ul>
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.</div>

Senior Staff Machine Learning Engineer

ServiceNow

<div>Company Description 
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today &mdash; ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500&reg;. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. 
Job Description 
What you get to do in this role:
The Advanced Technology Group (ATG) at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.
You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.<ul><li>
Build the best cloud-based AI/ML solutions to power intelligent enterprise services</li><li>
Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software</li><li>
Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users</li></ul> 

Qualifications 
To be successful in this role you have:<ul><li>
Expertise in Java or Python, OOP, Design Patterns, time and space-efficient algorithms</li><li>
Experience building new products that use challenging algorithms</li><li>
Expertise in coding efficient, object-oriented, modularized and quality software</li><li>
Knowledge of core AI/ML techniques and algorithms</li><li>
Knowledge of unit testing, profiling, and code tuning</li></ul>
For positions in this location, we offer a base pay of $201,300 - $352,300, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. 
Additional Information 
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. &copy;2025 Fortune Media IP Limited. All rights reserved. Used under license.</div>

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