Locations: US Remote, United States of AmericaSenior Machine Learning Engineer, Shopping - RemoteInterested in joining a dynamic remote first engineering team in a fast-paced environment full of greenfield problem-solving? Then Capital One Shopping might be the place for you. Join us in supporting a growth-stage line of business with a startup mindset as we build technology to save our customers money. As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll contribute to researching our next generation of models and recommendation systems to deliver value to our customers. You will use tools like Python, Pytorch, Transformers, language models, and other statistical tools.This is more than just a job; it's an opportunity to be part of a collaborative and forward-thinking community, where your contributions will make a significant impact in an ever-dynamic tech landscape. Join us as we push boundaries and redefine the future of our industry.What you’ll do in the role: <ul><li>The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:</li><li>Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. </li><li>Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).</li><li>Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. </li><li>Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. </li><li>Retrain, maintain, and monitor models in production.</li><li>Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.</li><li>Construct optimized data pipelines to feed ML models. </li><li>Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. </li><li>Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. </li><li>Use programming languages like Python, Scala, or Java. </li><li>Design and research new models using data scientist experience/expertise</li></ul>Basic Qualifications:<ul><li>Bachelor’s degree</li><li>At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)</li><li>At least 3 years of experience designing and building data-intensive solutions using distributed computing </li><li>At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) </li><li>At least 1 year of experience productionizing, monitoring, and maintaining models </li></ul>Preferred Qualifications:<ul><li>1+ years of experience building, scaling, and optimizing ML systems</li><li>1+ years of experience with data gathering and preparation for ML models</li><li>2+ years of experience developing performant, resilient, and maintainable code</li><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field </li><li>3+ years of experience with distributed file systems or multi-node database paradigms</li><li>Contributed to open source ML software </li><li>Authored/co-authored a paper on a ML technique, model, or proof of concept</li><li>3+ years of experience building production-ready data pipelines that feed ML models </li><li>Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance </li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization).The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.Remote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning EngineerCandidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<div><div><div><div>Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the <a href="https://www.capitalonecareers.com/benefits" target="_blank">Capital One Careers website</a>. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</div></div></div></div>This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at <a href="mailto:RecruitingAccommodation@capitalone.com" target="_blank">RecruitingAccommodation@capitalone.com</a>. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to <a href="mailto:Careers@capitalone.com" target="_blank">Careers@capitalone.com</a>Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Center 1 (19052), United States of America, McLean, VirginiaDistinguished Machine Learning Engineer As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

Apply below after reading through all the details and supporting information regarding this job opportunity.
In this role, you will be supporting the Bank Tech organization. You will lead development and implementation that will enable business initiatives, working with other leaders and teams across the enterprise to enable these solutions..
What you'll do in the role:
Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.

Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems.

Lead large-scale ML initiatives with the customer in mind.

Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.

Optimize data pipelines to feed ML models.

Use programming languages like Python, Scala, C/C++.

Leverage compute technologies such as Dask and RAPIDS

Evangelize best practices in all aspects of the engineering and modeling lifecycles.

Help recruit, nurture, and retain top engineering talent.

Basic Qualifications
Bachelor's degree.

At least 10 years of experience designing and building data-intensive solutions using distributed computing.

At least 6 years of experience programming in C, C++, Python, or Scala.

At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.

At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing

At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)

Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.

3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.

8+ years of experience within a large/data-intensive multi-line business environment.

Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.

Ability to communicate complex technical concepts clearly to a variety of audiences.

ML industry impact through conference presentations, papers, blog posts, or open source contributions.

Ability to attract and develop high-performing software engineers with an inspiring leadership style.

At this time, Capital One will sponsor a new applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
PDN-9d6fc27a-9a98-4140-acbf-46d1379aa5eb

ZS is a place where passion changes lives. As a management consulting and technology firm focused on transforming global healthcare and beyond, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop products that create value and deliver company results across critical areas of their business including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy and many more. Bring your curiosity for learning; bold ideas; courage and passion to drive life changing, impact to ZS. Our most valuable asset is our people. At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems-the ones that comprise us as individuals, shape who we are and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. Machine Learning Engineer AI Practice ZS AI Practice is building transformative AI-enabled data products and solutions. ZS suite of products and solutions include hyper-personalization, Customer journey design, AI guided selling, large-scale unstructured customer data mining with NLP and dynamic pricing. Our products and client focused solutions use state of the art ML and Deep Learning techniques and ML Engineering Platforms. What You'll Do <ul><li> Build , orchestrate, and monitor model pipelines including feature engineering, inferencing and continuous model training </li><li> Scaling machine learning algorithms to work on massive data sets and strict SLAs </li><li> Build & Enhance ML Engineering platforms and components </li><li> Implement ML Ops including model KPI measurements, tracking, data and model drift & model feedback loop </li><li> Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors </li><li> Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews </li><li> Collaborate with client teams and global development team to successfully deliver projects </li><li> Uses bug tracking, code review, version control and other tools to organize and deliver work </li> </ul><ul><li> Participate in scrum calls, and effectively communicate work progress, issues and dependencies </li><li> Consistently contribute to researching & evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of- concepts and creating prototype solutions. </li> </ul> What You'll Bring <ul><li> Bachelor's/ Master's degree with specialization in Computer Science, MIS, IT or another computer related discipline </li><li> 2-4 years' experience in deploying and productionizing ML models </li><li> Strong programming expertise in Python / PySpark </li><li> Experience in ML platforms like Dataiku, Sagemaker , MLFlow or other platforms </li><li> Experience in deploying models to cloud services like AWS, Azure, GCP </li><li> Expertise in crafting ML Models for high performance and scalability </li><li> Experience in implementing feature engineering, inferencing pipelines and real time model predictions </li><li> Experience in ML Ops to measure and track model performance </li><li> Good fundamentals of machine learning and deep learning </li><li> Knowledgeable of core Computer Science concepts such as common data structures , algorithms , and design patterns </li><li> Excellent oral and written communication skills </li> </ul> Additional Skills <ul><li> Experience with Spark or other distributed computing frameworks </li><li> Understanding ofDevOps,CI / CD, data security, experience in designing on cloudplatform </li><li> Experience in data engineering in Big Data systems </li></ul> Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Considering applying? At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact in global healthcare and beyond. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At: www.zs.com

Machine Learning Engineer Jobs in Philadelphia, PA

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Machine Learning Engineer Jobs in Philadelphia, PA

Senior Machine Learning Engineer Shopping RemoteDecember 19, 2024

Distinguished Machine Learning EngineerDecember 4, 2024

Machine Learning EngineerDecember 4, 2024

Quick filters

Top companies

Senior Machine Learning Engineer Shopping Remote
December 19, 2024

Distinguished Machine Learning Engineer
December 4, 2024

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December 4, 2024