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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

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 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

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer- Platform / Linux Engineering at JPMorganChase within the Corporate Sector- Infrastructure Platforms, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
As a Senior Platform Engineer within Electronic Trading Services Platforms, you will be a hands-on technical leader responsible for designing, building, and tuning the Linux-based compute and infrastructure platforms that power our low-latency electronic trading businesses. This is a deeply technical, engineering-first role: you will write code and automation, design new systems, architect novel deployment models, and drive latency out of the stack at the hardware, kernel, and network layers. You will also harness modern Agentic AI tooling to accelerate delivery and multiply your impact.
You will work directly with the Electronic Trading Lines of Business to align technical strategy with business goals, solve complex compute and performance-engineering challenges, and mentor partner technical teams. You will serve as an expert, hands-on advisor to peers, leadership, and stakeholders.
Job responsibilities<div>
</div><ul><li>Design, build, and operate high-performance Linux platforms for low-latency electronic trading, engineering from the hardware and kernel level up</li><li>
Architect new system designs and next-generation deployment models &mdash; including immutable infrastructure, containerization, and automated provisioning pipelines</li><li>
Perform deep performance engineering and latency optimization: kernel tuning, CPU isolation/pinning, NUMA awareness, IRQ affinity, kernel-bypass networking, and precision time synchronization</li><li>
Write production-quality code and automation to build tooling, eliminate manual toil, and improve platform reliability and speed</li><li>
Leverage Agentic AI tools and workflows to accelerate engineering tasks, automate research and remediation, and deliver against goals faster</li><li>
Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain</li><li>
Apply knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.</li><li>
Interface with hardware and software vendors on product roadmaps and to define the next generation of Electronic Trading Platform infrastructure</li><li>
Make decisions that influence teams' resources, budget, tactical operations, and the execution of processes and procedures</li><li>
Carry governance accountability for engineering decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations</li><li>
Deliver reusable technical solutions that can be leveraged across multiple businesses and domains and mentor and influence SRE, peer engineers, and senior stakeholders across business, product, and technology teams</li></ul>
Required qualifications, capabilities, and skills<div>
</div><ul><li>Formal training or certification on software engineering concepts and 5+ years applied experience</li><li>
Strong programming skills with the ability to build production-grade tooling and automation (e.g., Python, Go, Bash)</li><li>
Deep, hands-on Linux engineering expertise &mdash; administration, internals, performance tuning, and benchmarking, in areas such as Red Hat Enterprise Linux and proven experience engineering for low-latency, high-throughput environments (kernel tuning, CPU/NUMA optimization, precision timing)</li><li>
Hands-on experience with kernel-bypass networking, specifically Solarflare Onload and extensive experience with configuration management, in areas such as Chef or Ansible</li><li>
Hands-on experience applying Agentic AI tools (e.g., AI coding assistants and agent-based workflows) to accelerate engineering and operational tasks</li><li>
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security</li><li>
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls</li><li>
Solid understanding of IPv4 networking, including the OSI model, unicast/broadcast/multicast, routing, and network segregation mechanisms</li><li>
Experience designing CI/CD pipelines and infrastructure-as-code (e.g., Terraform)</li><li>
Practical cloud-native and container/orchestration experience (e.g., Docker, Kubernetes)</li><li>
Experience leading cross-functional teams of technologists, and hiring, developing, and recognizing talent</li></ul>
<div>Preferred qualifications, capabilities, and skills</div><div>
</div><ul><li>Experience with server hardware selection, BIOS/firmware tuning, and bare-metal provisioning for performance-sensitive workloads</li><li>
Familiarity with observability and telemetry stacks (e.g., Prometheus, Grafana, ELK) and understanding of standard cryptography (certificates, key pairs, secure communication, etc.)</li><li>
Experience with market-data and messaging technologies common to electronic trading (e.g., multicast market data, low-latency messaging buses)</li><li>
Experience with database management systems, preferably PostgreSQL</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
 
 
Our Global Technology Infrastructure group is a team of innovators who love technology as much as you do. Together, you'll use a disciplined, innovative and a business focused approach to develop a wide variety of high-quality products and solutions. You'll work in a stable, resilient and secure operating environment where you&mdash;and the products you deliver&mdash;will thrive. 
<div></div> 
<div><div>High Risk Roles (HRR) are sensitive roles within the technology organization that require high assurance of the integrity of staff by virtue of 1) sensitive cybersecurity and technology functions they perform within systems or 2) information they receive regarding sensitive cybersecurity or technology matters. Users in these roles are subject to enhanced pre-hire screening which includes both criminal and credit background checks (as allowed by law). The enhanced screening will need to be successfully completed prior to commencing employment or assignment.</div></div></div><div></div>

Senior Lead Software Engineer- Platform / Linux Engineering

Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 
 
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 
 
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 
 
 
 💻 Role
 
 
 
 Data is crucial to Whatnot&rsquo;s mission to bring people together through commerce.
 
 
 As our newest
 
 Data Engineer
 
 , you&rsquo;ll build and scale the systems that power data-driven decisions across the company. You&rsquo;ll work directly with stakeholders across the business &ndash; such as product, sales, marketing, finance, and trust teams &ndash; to design reliable data architectures, ship resilient pipelines, and create the foundational data products that power Whatnot&rsquo;s internal and external growth.
 
 
 
 On Any Given Day, You Will
 
 
 
 <ul>
 <li>
 Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
 </li>
 <li>
 Build mission-critical pipelines. Develop and operate streaming and batch data workflows that process high-volume events across multiple domains&mdash;user activity, transactions, experimentation, marketing performance, and operational telemetry&mdash;with tight guarantees for latency, completeness, and accuracy.
 </li>
 <li>
 Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
 </li>
 <li>
 Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
 </li>
 <li>
 Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
 </li>
 <li>
 Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, low-latency data through semantic layers, APIs, and real-time query systems.
 
 
 </li>
 </ul>
 Due to the cross-functional nature of this role, candidates will be matched to multiple teams based on need and experience, including product, analytics, or data platforms teams.
 
 
 
 👋 You
 
 
 
 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
 
 
 <ul>
 <li>
 Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
 </li>
 <li>
 Can design and implement data models using dimensional, Data Vault, or ledger-style techniques that support analytical and transactional workloads.
 </li>
 <li>
 Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
 </li>
 <li>
 Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
 </li>
 <li>
 Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
 </li>
 <li>
 Enjoy partnering across disciplines&mdash;engineering, product, analytics&mdash;to translate messy business requirements into elegant data systems.
 </li>
 <li>
 Thrive as a self-starter in a fast-moving environment, owning both the technical design and the operational outcomes of your work.
 
 
 </li>
 </ul>
 If designing the data backbone that powers Whatnot&rsquo;s growth, insights, and product innovation excites you, we&rsquo;d love to meet you.
 
 
 
 We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
 
 
 
 
 💰Compensation
 
 
 
 
 For Full-Time (Salary)
 
 
 
 
 US based applicants:
 
 $180,000/year to $260,000/year + benefits + equity.
 
 
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 
 
 
 🎁 Benefits
 
 
 
 <ul>
 <li>
 Generous Holiday and Time off Policy
 </li>
 <li>
 Health Insurance options including Medical, Dental, Vision
 </li>
 <li>
 Work From Home Support
 </li>
 <ul>
 <li>
 Home office setup allowance
 </li>
 <li>
 Monthly allowance for cell phone and internet
 </li>
 </ul>
 <li>
 Care benefits
 </li>
 <ul>
 <li>
 Monthly allowance for wellness
 </li>
 <li>
 Annual allowance towards Childcare
 </li>
 <li>
 Lifetime benefit for family planning, such as adoption or fertility expenses
 </li>
 </ul>
 <li>
 Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
 </li>
 <li>
 Monthly allowance to dogfood the app
 </li>
 <ul>
 <li>
 All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
 </li>
 </ul>
 <li>
 Parental Leave
 </li>
 <ul>
 <li>
 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
 </li>
 </ul>
 </ul>
 
 
 💛 EOE
 
 
 
 
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 
 
 Compensation Range: $180K - $260K
 
 
</div>

Data Engineer

Doppel

<div>
 
 Why Join Doppel
 
 
 
 Doppel is building the future of social engineering defense. Our AI-native platform uses agentic AI to protect executives, employees, customers, and brands from phishing, impersonation, fraud, and other AI-powered threats across digital channels. We help some of the world&rsquo;s most recognized brands detect and dismantle attacker infrastructure while strengthening employee resilience through threat-informed training and simulation. By unifying Digital Risk Protection, Human Risk Management and Email Security, Doppel connects threats into a real-time intelligence graph to power faster disruption, smarter defense, and modern security awareness at scale.
 
 
 Backed by leading investors including Andreessen Horowitz and Bessemer Venture Partners, and trusted by leading enterprises, Doppel is a rapidly growing Series C startup building the future of social engineering defense. Our team combines deep cybersecurity expertise, operational rigor, and startup velocity to solve some of the internet&rsquo;s most urgent trust and safety challenges.
 
 
 
 What We're Building
 
 
 
 We're building the AI-native social engineering defense platform.
 
 
 This means we're designing scalable systems that monitor billions of domains, social media accounts, apps, dark web forums, etc., and leverage AI agents to identify and neutralize digital threats.
 
 
 
 What We're Looking For
 
 
 
 We&rsquo;re looking for an experienced backend engineer to build out the infrastructure required to rapidly scale up our engineering organization. A few examples of the work we&rsquo;ve done recently:
 
 
 <ul>
 <li>
 Built a scalable data platform with a robust DBT transformation layer, enabling customers, engineers, and analysts to reliably model and query large-scale event data, track key product metrics, and power customer facing analytics.
 </li>
 <li>
 Launched a flexible notification system, delivering timely, reliable alerts across Slack, email, and other channels for internal and customer-facing use cases.
 </li>
 <li>
 Standardized core service patterns and shared business logic (auth, persistence, messaging), scaling them into reusable services that reduce duplication, ensure consistency, and enable product engineers to move faster as the company grows.
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 🚀 A mission-driven culture with low ego, high ownership, deep customer obsession, and exceptional talent density
 
 
 🍽️ Free lunch and dinner in the office
 
 
 🌴 Flexible PTO
 
 
 ✈️ Quarterly team offsites
 
 
 Join Doppel
 
 
 Doppel is the first platform built to dismantle digital deception at scale. We scan over 150 billion entities daily and deploy continuously adaptive AI SOC agents, paired with expert human analysts, to uncover and disrupt the infrastructure behind phishing, impersonation, and online fraud before attacks can spread. Our Threat Grid turns every customer signal into shared intelligence, making each disruption smarter, faster, and more effective.
 
 
 We&rsquo;re not just another cybersecurity company. We&rsquo;re defining the future of social engineering defense, where trust is protected, and deception becomes unprofitable. Backed by top-tier investors and trusted by some of the world&rsquo;s most recognized brands, Doppel is growing fast. If you&rsquo;re driven to solve real-world problems with bold technology, we&rsquo;d love to meet you.
</div>

Software Engineer, Platform

<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

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 New York, NY, USA; Mountain View, CA, USA; San Francisco, CA, USA
 
 .
 
 Minimum qualifications:
 
 
 
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 Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
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 1 year of experience designing data pipelines (ETL) and model data.
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 Experience analyzing data and creating reports, and with database query (e.g., SQL) and visualization tools (e.g., Tableau, dashboards).
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 Experience with one or more general purpose programming languages (e.g., Python, C/C++, Java).
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
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 Experience working in a data science environment, supporting feature engineering and model automation needs.
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 Experience working with big data tools, distributed computing and non-relational databases.
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 Structured thinking with ability to easily break down ambiguous problems and propose impactful data modeling designs.
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 Passion for analyzing large and complex data sets and converting them into the information which drive business decisions.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 The GCS Data Science team is working on challenging yet interesting problems for the GCS (Google Customer Solutions) division of Global Business Organization (GBO). Our goal is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.
 
 
 The Data Science Engineering (DSet) subteam is responsible for supporting data engineering needs for the GCS Data Science teams including building new data pipelines, automation, observability and reporting tools.
 
 
 As a Data Engineer, you will take on big data challenges in an agile way. In this role, you will use an analytical, data-driven approach to drive a deep understanding of our fast changing business. You will build data pipelines and reporting tools that enable our data scientists, through feature engineering, automated data extracts and wrangling needs, and scaled insights for both the data science team and our users.
 
 
 Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you&rsquo;ll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.
 
 
 Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
 US: $106000 - $151000 (USD) + 15% bonus target + equity + benefits
 
 
 
 Responsibilities
 
 
 
 Learn more about benefits at Google .
 
 
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 Build data pipelines, reports, best practices and frameworks that enable analysts and other stakeholders across the organization.
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 Use feature engineering to support data needs for ML/AI model development and subsequent scaling through ETL pipeline development.
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 Recognize and adopt best practices in developing pipelines, analytical insights including data integrity, test design, analysis, validation and documentation.
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 Design and develop scalable and actionable solutions (dashboards, automated collateral, web applications) that tell a story and provide insights to help our advertisers grow.
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 Work closely with various stakeholders to understand feature/tooling gaps and innovate on behalf of our customers.
 
 
 
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 </ul>
 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>

Data Engineer, GCS Data Science

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