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machine learning engineer

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

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

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Generative artificial intelligence is transforming how we build products, serve clients, and operate at scale. In the Chief Data and Analytics Office, you will help turn advanced models into dependable, secure, and high-performing production services. You will work with partners across machine learning, cloud engineering, and site reliability engineering to deliver solutions with clear return on investment. If you enjoy hands-on engineering, real-world constraints, and high-impact delivery, this role is for you.
As a Senior Associate, Generative AI Engineer in the Chief Data and Analytics Office, you will help design, build, and support production generative artificial intelligence products and reusable backend application programming interfaces used across the firm. You will combine large enterprise datasets with large language and multimodal models to deliver scalable, measurable solutions. You will collaborate closely with machine learning, cloud engineering, and site reliability engineering partners to ensure reliability, performance, and strong operational controls. You will contribute to technical design decisions, delivery planning, and continuous improvement of our platforms and products.
Job responsibilities
<ul><li>Build and operate production generative artificial intelligence services and reusable backend application programming interfaces for firmwide use</li>
<li>Combine enterprise data assets with large language and multimodal models to deliver high-quality user experiences</li>
<li>Design scalable architectures with clear interfaces and separation of concerns to enable broader developer adoption</li>
<li>Implement batch and real-time processing patterns to support high-throughput, low-latency use cases</li>
<li>Collaborate with cloud engineering and site reliability engineering partners to deliver resilient, observable systems</li>
<li>Translate research concepts into production-ready software through experimentation, evaluation, and iterative hardening</li>
<li>Optimize system performance, scalability, and cost across inference, storage, and compute</li>
<li>Define and track measurable outcomes, including objectives and key results aligned to business needs</li>
<li>Ensure responsible artificial intelligence practices, controls, and governance are embedded into delivery and operations</li>
<li>Troubleshoot production issues, drive root-cause analysis, and implement preventative improvements</li>
</ul>Required qualifications, capabilities, and skills
<ul><li>PhD in a quantitative discipline such as Computer Science, Mathematics, or Statistics, or equivalent practical experience</li>
<li>3+ years of experience as an individual contributor in machine learning engineering or applied machine learning software engineering</li>
<li>Demonstrated experience delivering production machine learning services in an enterprise environment, including being accountable for service health</li>
<li>Strong fundamentals in statistics, optimization, and machine learning theory with applied depth in natural language processing and/or computer vision</li>
<li>Hands-on experience building distributed, multi-threaded, and scalable systems (for example Ray, Horovod, or DeepSpeed)</li>
<li>Strong software engineering fundamentals, including data structures, algorithms, and software development lifecycle best practices</li>
<li>Experience designing and delivering service-oriented systems and application programming interfaces with scalability and performance requirements</li>
<li>Ability to define success metrics and write clear objectives and key results aligned to business expectations</li>
<li>Strong problem-framing skills to align machine learning solutions to business objectives and constraints</li>
<li>Excellent communication skills with the ability to influence and build trust across technical and non-technical stakeholders</li>
</ul>Preferred qualifications, capabilities, and skills
<ul><li>Experience designing and implementing pipeline workflows using directed acyclic graph frameworks (for example Kubeflow, DVC, or Ray)</li>
<li>Experience building batch and streaming microservices exposed via gRPC and/or GraphQL</li>
<li>Demonstrable experience with parameter-efficient fine-tuning, quantization, and quantization-aware fine-tuning for large language models</li>
<li>Experience with advanced prompting strategies such as chain-of-thought, tree-of-thought, or graph-of-thought approaches</li>
<li>Experience with multimodal large language model use cases (text plus image, speech, or video)</li>
<li>Experience partnering closely with cloud engineering and site reliability engineering teams on production readiness and operations</li>
<li>Experience measuring and improving model quality using offline evaluation and production monitoring</li>
</ul>#LI-RB3
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
 
 
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.</div>

Generative AI - Senior Associate

Stott and May

<div>
 
 Senior Data Scientist
 
 
 
 Manufacturing | Azure, Databricks &amp; Microsoft Fabric
 
 
 
 
 
 
 Our manufacturing client is looking for a
 
 Senior Data Scientist
 
 to help build data-driven solutions that improve operations and support business decision-making. You'll work with cross-functional teams to develop predictive models, analyze manufacturing data, and deliver insights using a modern Microsoft technology stack.
 
 
 
 
 
 Responsibilities
 
 <ul>
 <li>
 Develop machine learning models and analytical solutions to solve business problems.
 </li>
 <li>
 Analyze manufacturing, operational, and supply chain data to identify trends and opportunities.
 </li>
 <li>
 Build predictive models for forecasting, optimization, and operational reporting.
 </li>
 <li>
 Work with business stakeholders to understand requirements and translate them into data science solutions.
 </li>
 <li>
 Collaborate with Data Engineers to prepare and transform data for modeling.
 </li>
 <li>
 Present findings and recommendations to technical and non-technical audiences.
 </li>
 <li>
 Support the deployment and ongoing improvement of machine learning models.
 </li>
 </ul>
 
 
 
 
 Required Skills
 
 <ul>
 <li>
 5+ years of experience as a Data Scientist.
 </li>
 <li>
 Strong Python and SQL skills.
 </li>
 <li>
 Experience building and deploying machine learning models.
 </li>
 <li>
 Hands-on experience with
 
 Azure Databricks
 
 .
 </li>
 <li>
 Experience with
 
 Microsoft Fabric
 
 or other Microsoft analytics tools.
 </li>
 <li>
 Experience working with Azure cloud services.
 </li>
 <li>
 Strong understanding of statistics, predictive modeling, and data analysis.
 </li>
 <li>
 Excellent communication and stakeholder management skills.
 </li>
 </ul>
 
 
 
 
 
 Fully Remote
 
 
 
 
 12-month contract with possible extension
 
 
 
 
 40hr/week
 
 
 
 
 95-125/hourly W2 or LLC
 
 
 
 (There are
 
 no
 
 C2C options for this role)
 
 
 
 
</div>

Senior Data Scientist

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

<div>Company Description 
Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We&rsquo;re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.
Sia&rsquo;s AI &amp; Data Business Unit is the powerhouse of our firm&rsquo;s innovation&mdash;merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&amp;D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia&rsquo;s AI &amp; Data team, you&rsquo;ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. 
Job Description 
To support its growth, Sia is recruiting a Data Scientist Consultant with a strong interest in Risk, Compliance and Regulatory topics and challenges.
Reporting to Sia's Data Science teams, your role is to support our clients' operational teams and compliance departments in defining their data needs, analyzing their data, deploying data science algorithms, and AI agents and providing strategic decision support.
These engagements require the implementation of complex analyses to support our clients, notably in:<ul><li>
Forward-Deployed Engineering</li><li>
Generative AI, Machine Learning &amp; Statistics</li><li>
Data Analysis for strategic support</li><li>
Data Engineering &amp; DevOps</li><li>
Data Transformation &amp; Acculturation</li></ul>
A few examples of engagements:<ul><li>
Predictive compliance risk monitoring: Building automated data pipelines and dashboards to track operational metrics and forecast the future health of compliance workstreams, enabling proactive risk identification and mitigation.</li><li>
AI-powered regulatory intelligence: Designing and deploying a GenAI-driven system that monitors regulatory change in real time, structures obligations, maps them automatically to internal policies and controls, scores compliance gaps, and orchestrates remediation workflows - all with a full source-of-truth audit trail for compliance, risk, and legal teams.</li><li>
Analytics/ML models for AML compliance: Built and refined ML models to automate due diligence and ID verification workflows, reducing manual review time. Managed third-party data integration and collaborated with Legal and Engineering to ensure compliant deployment.</li></ul>
As part of the firm's internal activities, your contribution will focus on the following areas:<ul><li>
Developing or strengthening our offerings through training, working groups, and internal/external materials.</li><li>
Our publication strategy (sector blogs, studies, press coverage). \</li><li>
Business development, by contributing to the definition of client needs and participating in sales activities.</li></ul>
Key Responsibilities:<ul><li>
Partner with our clients' leadership teams, engineers, program managers, and data analysts to understand data needs.</li><li>
Identify, acquire, process, and explore relevant data sources.</li><li>
Analyze large amounts of structured and unstructured information to discover trends and patterns.</li><li>
Use your data analytics and data science expertise to derive valuable insights from datasets, and build predictive models and machine learning algorithms.</li><li>
Design, build, fine-tune, and deploy LLM-based systems using models such as GPT, Claude, Gemini, Llama, and Mistral.</li><li>
Develop GenAI-powered applications (self-managed and API-based) that meet real business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses).</li><li>
Design and optimize prompting strategies (few-shot, Chain/Tree-of-Thought, ReAct, self-reflection, guardrails) to improve reliability and control.</li><li>
Communicate at scale through multiple mediums: presentations, dashboards, datasets, bots, and more.</li><li>
Propose solutions and strategies to business challenges.</li><li>
Collaborate with engineering and product development teams.</li><li>
Work across a broad range of partners and projects, delivering models, algorithms, datasets, measurements, services, tools, and processes.</li></ul> 

Qualifications 
<ul><li>
Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field.</li><li>
2+ years of experience as a Data Scientist or Data Analyst.</li><li>
Strong programming skills, particularly Python and SQL.</li><li>
Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.).</li><li>
Experience with cloud platforms (AWS, Azure, or GCP).</li><li>
Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, etc.).</li><li>
Excellent communication skills, with the ability to explain complex technical concepts simply.</li></ul>
Preferred technical experience:<ul><li>
Experience building agentic AI systems.</li><li>
Good understanding of machine learning techniques.</li><li>
Good understanding of statistical techniques and concepts.</li><li>
Experience with data visualization tools.</li><li>
Experience developing conversational AI systems / chatbots.</li><li>
Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as the Model Context Protocol (MCP).</li><li>
Experience deploying models at scale in production environments.</li></ul>
Preferred industry sector experiences<ul><li>
Regulatory Obligations Management: Analyze and document legal/regulatory requirements to maintain and update the client's RCM obligations library</li><li>
Control Design &amp; Implementation: Design and implement operational controls and compliance frameworks to ensure regulatory adherence</li><li>
Risk Assessment &amp; Testing: Lead RCSAs, thematic reviews, and control testing to identify compliance and operational gaps</li><li>
Regulatory Analysis &amp; Strategy: Interpret emerging regulatory trends and enforcement actions to inform compliance strategy</li><li>
Compliance Best Practices: Develop and maintain compliance best practices</li><li>
Regulatory Interpretation &amp; Controls Mapping: Interpret laws and regulations to assess applicability and map obligations to controls</li><li>
Risk &amp; Compliance Transformation: Support transformation engagements across first-line (controls design/testing) and second-line (risk, compliance) functions</li></ul> 

Additional Information 
Compensation &amp; Benefits
Sia invests in total rewards that support how our people work, live, and grow.
Compensation<ul><li>
Base Salary: $95,000-116,000. Actual compensation within this range will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by applicable law.</li><li>
Annual Performance Bonus</li></ul>
Benefits<ul><li>
Medical, dental, and vision; company-paid life and AD&amp;D; voluntary supplemental insurance and EAP</li><li>
401(k) with company match and immediate vesting; HSA and FSA options</li><li>
College savings and student loan repayment programs</li><li>
Paid parental leave; generous PTO, nine company holidays, and one floating holiday</li><li>
Cell phone stipend; well-being and professional development programs</li></ul>
Benefits are subject to applicable plan terms and eligibility requirements.
Workplace 
Sia values in-person collaboration. When serving clients, consultants may be required to work onsite at a client location based on engagement needs. Between client engagements, consultants are expected to work from a Sia office or approved coworking location at least three days per week. Candidates should reside within a reasonable commuting distance of a Sia office or approved coworking location. Sia maintains offices and coworking arrangements across multiple U.S. markets, including New York City, Charlotte, Greater Seattle, San Francisco Greater Bay Area, Los Angeles, Houston, Atlanta, Baltimore, Chicago, Washington D.C.
Work Authorization
Applicants must be legally authorized to work in the United States at the time of application and throughout their employment. This position is not eligible for employment visa sponsorship now or in the future.
Our Commitment
At Sia, we believe in fostering a diverse, equitable, and inclusive culture where our employees and partners are valued and thrive in a sense of belonging.<div></div>
Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.</div>

Consultant – Compliance Data Science & AI

FTI Consulting, Inc.

<div>Who We Are 
 
FTI Consulting is the leading global expert firm for organizations facing crisis and transformation. We work with many of the world&rsquo;s top multinational corporations, law firms, banks and private equity firms on their most important issues to deliver impact that makes a difference. From resolving disputes, navigating crises, managing risk and optimizing performance, our teams respond rapidly to dynamic and complex situations.
 
 
At FTI Consulting, you&rsquo;ll work side-by side with leaders who have shaped history, helping solve the biggest challenges making headlines today. From day one, you&rsquo;ll be an integral part of a focused team where you can make a real impact. You&rsquo;ll be surrounded by an open, collaborative culture that embraces diversity, recognition, professional development and, most importantly, you.
 
 
Are you ready to make your impact?
About the Role
The eDiscovery Innovation Team at FTI Consulting is expanding rapidly as we make key investments in applying Generative AI and Machine Learning to some of the world&rsquo;s biggest disputes, investigations, and litigations.
Applied Scientists should have a pragmatic approach to problem-solving and be capable of developing end-to-end solutions that clients can rely on in production. They should be capable of challenging their own work and finding a balance between perfection and practicality.
What You&rsquo;ll Do
<ul><li>Prototype, validate, and implement AI/ML solutions on diverse and constantly evolving client datasets
</li><li>Apply the latest LLMs in Azure OpenAI and AWS Bedrock to tasks like:
<ul><li>summarization
</li><li>classification
</li><li>entity extraction
</li><li>text-to-query language generation
</li></ul></li><li>Develop RAG pipelines, semantic search, and hybrid search
</li><li>Create and implement new metrics, evaluation pipelines, and internal training/test datasets
</li><li>Survey, test, and critique use of emerging technologies to enhance existing solutions and develop new capabilities.
</li><li>Share your work with clients and colleagues and to both technical and non-technical audiences. You will help lead the way in the adoption of AI across the enterprise.
</li><li>Build industry expertise and become a contributor in deploying our solutions into client architectures.
</li></ul>How You&rsquo;ll Grow
We are committed to investing and supporting you in your professional development and we have developed a range of programs focused on fostering leadership, growth and development opportunities. We aim to promote continuous learning and individual skills development through on-the-job learning, self-guided professional development courses and certifications. You&rsquo;ll be assigned a dedicated coach to mentor, guide and support you through regular coaching sessions and serve as an advocate for your professional growth. As you progress through your career at FTI Consulting, we offer tailored programs for critical professional milestones to ensure you are prepared and empowered to take on your next role.
What You&rsquo;ll Need to Succeed
Basic Qualifications
<ul><li>2+ years of practical, relevant experience building NLP/IR/ML systems, from ideation to production
</li><li>Bachelor&rsquo;s degree or relevant experience
</li><li>High level of analytical programming competency (e.g., Python, R)
</li><li>Hands-on development experiment with LLMs, deep learning NLP models and traditional ML techniques
</li><li>Ability to travel to clients and FTI office(s) as needed
</li><li>Applicants must be currently authorized to work in the United States on a full-time basis; this position does not provide visa sponsorship
</li></ul>Preferred Qualifications
<ul><li>Experience with Elasticsearch, OpenSearch, or other Lucene technologies
</li><li>Experience with C# and .NET
</li><li>Experience with Docker and an understanding of Kubernetes
</li><li>Solid software engineering skills for prototyping
</li><li>Experience with working in cloud architectures (AWS, Azure, etc.)
</li><li>Experience in a customer-facing role 
</li></ul> 
FTI Consulting is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation. 
 
Compensation
Minimum Pay: $101,500
 
Maximum Pay: $142,000
Compensation Disclosure: The compensation range reflects potential base salary for the role. Actual compensation is determined based on a wide array of relevant factors including market considerations, business needs, and an individual&rsquo;s location, skills, level of experience, and qualifications.</div>

eDiscovery Data Scientist | Technology Consulting

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