software engineer

ai engineer

ai engineer ii

backend engineer

bms field engineer

ml engineer

Capital One

<div>Lead Machine Learning Engineer, Card Tech
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&rsquo;ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You&rsquo;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 have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What You&rsquo;ll Do:
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:<ul><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></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)</li><li>
At least 4 years of experience programming with Python, Scala, or Java</li><li>
At least 2 years of experience building, scaling, and optimizing ML systems</li></ul>
Preferred Qualifications:<ul><li>
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field</li><li>
3+ years of experience building production-ready data pipelines that feed ML models</li><li>
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow</li><li>
2+ years of experience developing performant, resilient, and maintainable code</li><li>
2+ years of experience with data gathering and preparation for ML models</li><li>
2+ years of people leader experience</li><li>
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation</li><li>
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform</li><li>
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance</li><li>
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents</li><li>
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion</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, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
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, NY: $215,200 - $245,600 for Lead 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&rsquo;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 the Capital 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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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&rsquo;s Fair Chance Act; Philadelphia&rsquo;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).</div>

Lead Machine Learning Engineer, Card Tech

Mirage

<div>Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would &mdash; dramatically improving productivity for experienced teams, while making video creation accessible to anyone. 
 
We&rsquo;re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you&rsquo;ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. 
More about us
Product (Captions by Mirage)
Research (Seeing Voices, technical-white-paper)
Updates (Mirage on X / twitter)
TechCrunch, Forbes AI 50, Fast Company (press) 
Our Investors
We&rsquo;re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.
Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
About the Role 
Mirage is seeking an ML Engineer to push the boundaries of large language models for multimodal creative tasks. You'll develop new approaches for building and extending agentic systems that understand and operate over complex, real-world data, particularly video.
This role focuses on advancing agent capabilities, improving reasoning and control, and enabling new forms of interaction between language models and time-based media.
Responsibilities<ul><li>
Design and build end-to-end agentic systems for creative tasks</li><li>
Develop novel approaches for training and adapting the large language models that power these agents</li><li>
Design new objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability</li><li>
Explore multimodal reasoning and structured generation for creative control</li><li>
Run systematic experiments to evaluate and improve agent performance in real-world tasks</li><li>
Design evaluation frameworks for agentic workflows in video analysis and editing</li><li>
Analyze failure modes across the full agent loop (planning, tool use, execution) and iterate on improvements</li></ul>
What makes you a great fit<ul><li>
BS/MS/PhD in CS, ML, or related field</li><li>
Strong track record building production ML systems or agentic pipelines</li><li>
Deep understanding of transformers and modern LLM techniques</li><li>
Experience with fine-tuning, alignment, or post-training methods, especially for adapting models to generate structured outputs or drive tool use</li><li>
Comfort owning the full stack, from model-level experiments to deployed agent systems</li><li>
Strong experimental rigor and good taste for what makes agents actually work in practice</li></ul><h3 class="jobSectionHeader">
Benefits:</h3><ul><li>
Comprehensive medical, dental, and vision plans</li><li>
401K with employer match</li><li>
Commuter Benefits</li><li>
Catered lunch multiple days per week</li><li>
Dinner stipend every night if you're working late and want a bite!
</li><li>Grubhub subscription</li><li>
Health &amp; Wellness Perks</li><li>
Multiple team offsites per year with team events every month</li><li>
Generous PTO policy</li></ul>
Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please note benefits apply to full time employees only.
Compensation Range: $175K - $275K</div>

Research Engineer, Agentic Systems

Uber

<div>About the Role
 
 
Uber Freight Marketplace is building the next generation of logistics technology by leveraging Uber's proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber's mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms.
 
 
We are looking for a highly motivated Machine Learning Engineer to join Uber's Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity.
 
 
What You'll Do
 
 
This role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected.
 
 
Basic Qualifications
<ul><li>4+ years of experience developing ML models to solve business problem.
</li><li>Bachelor's degree in Computer Science, Computer Engineering, or related fields.
</li><li>Familiar with modern AI/ML frameworks (e.g., PyTorch).
</li></ul>Preferred Qualifications
<ul><li>Product experience will be a big plus for this role. Adaptive development of ML models to the business context is critical.
</li><li>Previous experience with state-of-the-art marketplace technology is preferred.
</li>Experience with causal inference and constrained optimization 
<li>
</li></ul> 
 
For Chicago, IL-based roles: The base salary range for this role is USD $182,000 per year - USD $202,000 per year. 
 
For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. 
 
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. 
 
For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. 
 
For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. 
 
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. 
 
Ready to Ride? 
 
This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. 
 
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
 
 
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. 
 
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.</div>

Senior Machine Learning Engineer

<div>Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would &mdash; dramatically improving productivity for experienced teams, while making video creation accessible to anyone. 
 
We&rsquo;re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you&rsquo;ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. 
More about us
Product (Captions by Mirage)
Research (Seeing Voices, technical-white-paper)
Updates (Mirage on X / twitter)
TechCrunch, Forbes AI 50, Fast Company (press) 
Our Investors
We&rsquo;re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.
Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
About the Role 
Mirage is seeking an ML Engineer to build and scale the systems powering our video generation models. You&rsquo;ll work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.
This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation.
Responsibilities<ul><li>
Train and optimize large-scale video and multimodal models</li><li>
Improve efficiency across training and inference (memory, latency, cost)</li><li>
Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation</li></ul><ul><li>
Build and maintain distributed training systems</li><li>
Optimize GPU utilization, parallelism, and throughput</li><li>
Develop tooling for experimentation, evaluation, and debugging</li></ul><ul><li>
Translate research models into robust, production-ready systems</li><li>
Monitor and improve model performance in real-world usage</li></ul>
What makes you a great fit<ul><li>
BS/MS/PhD in CS, ML, or related field</li><li>
2+ years of professional industry experience</li><li>
Strong experience in deep learning systems and infrastructure</li><li>
Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.)</li></ul><ul><li>
Experience scaling and optimizing large models under low-latency inference constraints</li><li>
Strong debugging and performance profiling skills</li><li>
Ability to move quickly from prototype to production</li></ul><h3 class="jobSectionHeader">
Benefits:</h3><ul><li>
Comprehensive medical, dental, and vision plans</li><li>
401K with employer match</li><li>
Commuter Benefits</li><li>
Catered lunch multiple days per week</li><li>
Dinner stipend every night if you're working late and want a bite!
</li><li>Grubhub subscription</li><li>
Health &amp; Wellness Perks</li><li>
Multiple team offsites per year with team events every month</li><li>
Generous PTO policy</li></ul>
Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please note benefits apply to full time employees only.
Compensation Range: $175K - $275K</div>

Research Engineer, Generative Video

Google

<div>Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; New York, NY, USA.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience. 
</li>
<li>5 years of experience programming in Python or C++.</li>
<li>3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).</li>
<li>3 years of experience testing, maintaining, or launching software products.</li>
<li>1 year of experience with software design and architecture.</li>
<li>1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master's degree or PhD in Computer Science or related technical field. 
</li>
<li>5 years of experience with data structures and algorithms.</li>
<li>1 year of experience in a technical leadership role. 
</li>
<li>Experience developing accessible technologies. 
</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.

Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Write and test product or system development code. 
</li>
<li>Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,) 
</li>
<li>Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. 
</li>
<li>Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality. 
</li>
<li>Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains. 
</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 Software Engineer, AI/ML GenAI, Google Cloud

JPMorganChase

<div>JOB DESCRIPTION 
 
 
As part of the Commercial &amp; Investment Bank, J.P. Morgan Payments enables organizations of all sizes to execute transactions efficiently and securely, transforming the movement of information, money and assets. We tackle complex challenges at every stage of the payment lifecycle and our industry-leading solutions facilitate seamless transactions across borders, industries and platforms. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion.
As a Vice President Applied AI/ML Scientist within our payment solutions team, you will be instrumental in utilizing artificial intelligence and machine learning technologies to augment our services and stimulate business expansion. Your role will involve researching, experimenting, developing, and implementing high-quality machine learning models, services, and platforms to streamline payment processes, bolster fraud detection, and enrich customer experience. You will also be tasked with designing and executing highly scalable and dependable data processing pipelines, conducting analysis, and deriving insights to boost and optimize business outcomes. Collaborating with cross-functional teams to pinpoint opportunities for AI/ML applications within the payment's ecosystem will also be a part of your responsibilities.
Job Responsibilities:
<ul><li>Actively collaborate with Product, Technology, and other cross-functional teams to gain a deep understanding of complex business problems and formulate data-driven solutions to address these challenges in key areas of the payments' domain.
</li><li>Design, develop, and deploy agentic systems using Large Language Models (LLM), machine learning and other AI solutions that meet success metrics aligned with business goals, while considering constraints such as model complexity, scalability, and latency.
</li><li>Partner with Risk and Compliance teams to ensure comprehensive model documentation, track performance metrics, and maintain adherence to regulatory compliance standards.
</li><li>Translate model outcomes into business impact metrics and communicate complex concepts to senior management and stakeholders.
</li></ul>Required qualifications, capabilities, and skills:
<ul><li>Master's degree in a quantitative discipline (e.g., Computer Science, Data Science, Mathematics/Statistics, or Operations Research) with a minimum of 6 years of industry experience. Experience with Shell Scripting, Jupyter notebook/Lab, SQL, PySpark, and AWS Cloud Services is required.
</li><li>Proficient in Python with hands-on experience in Machine learning and Deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Experience with Jupyter Notebook/Lab is essential.
</li><li>Extensive knowledge in the design and development of agentic systems and the tooling ecosystem such as LangChain, LangGraph, Model Context Protocol (MCP), DSPy, etc.
</li><li>Solid Understanding of algorithms in machine learning, AI, and neural network, including Large Language Models (LLM) and Generative AI as well as familiarity with state-of-the-art practices and advancements in these domains.
</li><li>Ability to set the analytical direction for projects, transforming vague business questions into structured analytical plans. You possess strong cognitive and communication skills, characterized by clear and articulate expression. You excel at identifying core issues, bringing order to chaos, synthesizing insights, and driving decisive outcomes.
</li><li>Extensive experience in Natural Language Processing (NLP) or Large Language Models (LLM),or Computer Vision and other machine learning techniques, including classification, regression algorithms.
</li></ul>Preferred Qualifications, capabilities and skills
<ul><li>Experience in the financial services industry, particularly within investment banking operations.
</li><li>Cloud computing: Amazon Web Service, Azure, Docker, Kubernetes, DataBricks, Snowflakes.
</li><li>Familiarity with inference-time algorithms such as Chain of Thought and sampling, etc.
</li></ul>ABOUT US 
 
 
<div><div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>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.
<div>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' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM
 
 
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Applied AI/ML Lead

Capgemini

<div><div><div><div>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
<div><div><div><h2 class="jobSectionHeader">Job Description</h2>
</div><div>Required Skills: Python, Machine Learning, Deep Learning, PyTorch, TensorFlow, Keras, Generative AI, Large Language Models (LLMs), Prompt Engineering, Fine-Tuning Techniques (LoRA, QLoRA), Hugging Face, LangChain, LlamaIndex, Retrieval-Augmented Generation (RAG), Vector Databases, Hybrid Search Techniques, NLP, Data Processing, REST APIs, Git, Agile/Scrum.
Preferred Skills: Agentic AI Frameworks, AI Model Evaluation, MLOps, Azure OpenAI, AWS Bedrock, Databricks, Streamlit, FastAPI, Docker, Kubernetes, Banking or Financial Services Domain Experience.
Job Responsibilities:
Design, develop, and deploy AI/ML and Generative AI solutions using Python, build and fine-tune machine learning and large language models using frameworks such as PyTorch, TensorFlow, and Keras, develop RAG-based applications using LangChain, Hugging Face, and LlamaIndex, implement and optimize vector search and hybrid search solutions, perform model training, evaluation, and fine-tuning using techniques such as LoRA and QLoRA, develop APIs and AI-powered services, integrate AI models with enterprise applications, ensure model performance, scalability, and reliability, collaborate with business and technology teams to translate requirements into AI solutions, and participate in Agile development, testing, deployment, and support activities.
</div></div></div>The base compensation range for this role in the posted location is: $106230 to $145000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul>Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</div></div></div></div>

AI/ML, GenAI & Python Developer - Onsite NJ

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