ml engineer

MetaVoice

<div>
 
 At MetaVoice, our goal is an
 
 AI for voice conversations that's as natural as talking to a person.
 
 
 
 
 
 
 Today's voice AI fails at real-world conversations. It&rsquo;s slow, turn-based like a walkie-talkie, breaks with interruptions, and doesn&rsquo;t understand emotion.
 
 
 
 
 
 Developers can't build compelling experiences and users disengage. This limits voice AI to simple receptionist tasks and basic customer support, blocking meaningful services (sales, therapy, coaching) where dialogue and emotional intelligence matter most. Scaling current tech does not work.
 
 
 
 
 
 We're building voice AI that's as natural as talking to a person. Our approach is a duplex speech-to-speech model that learns conversational behaviour directly from data.
 
 
 
 
 
 MetaVoice is founded by:
 
 <ul>
 <li>
 Sid, founding engineer at Wayve.ai ( $2.5B+ raised)
 </li>
 <li>
 Vatsal, co-created Alexa&rsquo;s first AI voice.
 </li>
 </ul>
 
 
 
 
 We&rsquo;re passionate about building products people truly love.
 
 
 
 
 
 
 The role
 
 
 
 This is a founding engineer role owning the ML data &amp; evaluation platform that model development runs on.
 
 
 
 
 
 
 Who we're looking for
 
 
 
 You&rsquo;ve worked on distributed ML infra and understand that model quality is often a data problem. You:
 
 <ul>
 <li>
 Have a track record of taking initiative and learning things quickly.
 </li>
 <li>
 Care deeply about the people using the systems you build, whether they're researchers, operators or customers
 </li>
 <li>
 Have built something yourself (startup, side project, etc) or worked in an early-stage startup
 </li>
 </ul>
 
 
 
 
 
 What you've done
 
 
 <ul>
 <li>
 Built distributed ML data pipelines to generate datasets for training and evaluation, including curation, sampling and slicing.
 </li>
 <li>
 Built and operated MLOps infrastructure to train, evaluate and serve ML models, including versioning, orchestration and observability.
 </li>
 <li>
 Built eval systems to measure model quality and catch regressions.
 </li>
 <li>
 Developed internal tools and workflows for researchers and operators to explore data and iterate fast.
 </li>
 </ul>
 
 Strong plus:
 
 <ul>
 <li>
 Designed data flywheels: automated data collection and model update loops.
 </li>
 <li>
 Designed evaluation frameworks: automated or human-in-the-loop
 </li>
 <li>
 Experience with speech, audio, or conversational datasets
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Change the world (when we succeed)
 </li>
 <li>
 Environment to do the best work of your life.
 </li>
 <li>
 Small, humble and talent dense team.
 </li>
 <li>
 Opportunity to make cutting-edge research work in real-world scenarios.
 </li>
 <li>
 Work with 100+ TBs of data and 10B+ parameter models.
 </li>
 </ul>
 
 
 
 
 
 Culture
 
 
 <ul>
 <li>
 We're an in-person team in San Francisco &amp; love working together. It helps us learn from one another and make decisions quickly.
 </li>
 <li>
 We ship fast &amp; obsess over making customers happy.
 </li>
 <li>
 We offer high autonomy, allowing everyone to do their best work.
 </li>
 </ul>
 
 
 
 
 
 Compensation &amp; Benefits
 
 
 <ul>
 <li>
 Significant equity as a founding team member.
 </li>
 <li>
 $180K-300K base.
 </li>
 <li>
 Immigration support, we are immigrants ourselves.
 </li>
 <li>
 Fully covered medical, dental, and vision insurance
 </li>
 </ul>
 
 
 
 
 
 Interview Process
 
 
 
 We move with speed, and aim to go from first interview to offer within a week.
 
 <ul>
 <li>
 
 Vibe check, 30 mins:
 
 chat with one of the founders about the mission, product and your background
 </li>
 <li>
 
 Technical Interview: 30 mins
 
 </li>
 <li>
 
 Culture interview: 30 mins
 
 </li>
 <li>
 
 Onsite co-work:
 
 Spend half a day with us. We'll build and iterate on a problem together.
 </li>
 </ul>
 
 
</div>

ML Platform Engineer (Data & Evals)

Information Technology Senior Management Forum

<div><div>Posted Date
6/29/2026
</div><div>Description
<div>Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI 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).
Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI 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>
</div><div>Salary
229,900.00 - 262,400.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)

Smvsoft LLC

Founding Engineer - Applied AI San francisco, CA (Full time)- In-Office$180k-$230k per annumNO C2CAbout the RoleHiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.Key Responsibilities<ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul>RequirementsMust-Have<ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul>Nice-to-Have<ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul>Pay: $180,000.00 - $230,000.00 per yearWork Location: In person

Founding Engineer - Applied AI

Cognizant

About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.
 By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery models. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.
 <ul>
<li>Please note, this role is not able to offer visa transfer or sponsorship now or in the future*</li>
</ul>
Job Summary
 We are seeking an AI Architect to lead the design, development, and delivery of enterprise-scale Generative AI and agentic AI solutions on Google Cloud Platform. This role focuses on defining end-to-end AI/ML architecture strategy, building scalable LLM and multi-agent systems, and driving innovation using Vertex AI. You will play a key role in enabling intelligent automation through advanced AI frameworks while ensuring production readiness, governance, and business alignment. The position requires strong technical leadership, deep hands-on expertise, and client-facing consulting experience.
 
In this role, you will: 
<ul>
<li>Define and lead enterprise AI architecture strategy for Generative AI and agentic AI solutions on GCP.</li>
<li>Architect and implement LLM-based applications using Vertex AI services including Model Garden, Gemini API, and custom training pipelines.</li>
<li>Design and develop multi-agent AI systems using Google ADK or equivalent frameworks (LangGraph, CrewAI, AutoGen).</li>
<li>Build scalable Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Search, Vector Search, and BigQuery.</li>
<li>Develop and manage LLMOps pipelines covering model versioning, evaluation, fine-tuning (SFT/RLHF/PEFT), and deployment using Vertex AI Pipelines.</li>
<li>Leverage GCP-native services (Cloud Run, GKE, Dataflow, Pub/Sub, Apigee) to design and implement AI-first platforms.</li>
<li>Provide technical leadership, mentor teams, and conduct architecture reviews ensuring governance and responsible AI practices.</li>
<li>Define reusable design patterns, best practices, and reference architectures for LLM and agentic AI solutions.</li>
<li>Collaborate with clients and stakeholders to define AI strategy, lead PoCs, solution demos, and RFP/RFI responses.</li>
<li>Drive innovation adoption by evaluating emerging AI tools, models, frameworks, and enterprise AI capabilities.</li>
</ul>
What you need to have to be considered
 <ul>
<li>15+ years of experience in AI/ML, cloud architecture, or enterprise digital transformation roles.</li>
<li>Strong hands-on expertise in Google Cloud Platform including Vertex AI, BigQuery, Dataflow, GKE, Cloud Run, Pub/Sub, and IAM.</li>
<li>Proven experience designing and delivering production-grade Generative AI and LLM-based applications.</li>
<li>Deep knowledge of RAG architectures, embeddings, vector databases, prompt engineering, and model evaluation strategies.</li>
<li>Experience building agentic AI systems using ADK or frameworks like LangGraph, CrewAI, or AutoGen.</li>
<li>Strong programming skills in Python with experience in MLOps tools (Vertex AI Pipelines, MLflow, Kubeflow).</li>
<li>Solid understanding of containerization (Docker, Kubernetes) and CI/CD pipelines.</li>
<li>Strong leadership, stakeholder engagement, and consulting experience working with enterprise clients.</li>
<li>GCP certifications (Professional Architect / ML Engineer) and experience in regulated industries are a plus.</li>
</ul>
#LI-EF1
 #CB
 #Ind123
 Applications will be accepted until 10 Jul 2026.
 
Salary and Other Compensation: 
The annual salary for this position is between $[174,500 - 204,500] depending on experience and other qualifications of the successful candidate.
 This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
 Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
 <ul>
<li>Medical/Dental/Vision/Life Insurance</li>
<li>Paid holidays plus Paid Time Off</li>
<li>401(k) plan and contributions</li>
<li>Long-term/Short-term Disability</li>
<li>Paid Parental Leave</li>
<li>Employee Stock Purchase Plan</li>
</ul>

Sr. AI Architect

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Interactive Video Service (Amazon IVS) is AWS's fully managed live streaming service, built on the same battle-tested technology that powers Twitch and trusted by thousands of enterprises across gaming, social, live commerce, sports, and entertainment. 
 
Our mission: enable developers to build communities around live video. We handle everything from ingest to processing to delivery at global scale, so developers can focus on creating interactive, engaging live experiences for their audiences. Whether you're streaming to tens of millions of concurrent viewers or just getting started, Amazon IVS removes the complexity so developers can move fast. 
 
As a Software Dev Engineer on the IVS's Data team, you will be responsible for empowering internal teams and IVS customers with the data they need to make key operational and business decisions. We operate petabyte-scale data infrastructure for collecting, processing, and warehousing IVS data. We support streaming and batch pipelines to facilitate analytics, reporting, and ML workloads. We offer analytics tools and data products designed to make it easy and fast for our customers to extract the insights they need from their data. 
 
Key job responsibilities 
<ul><li>Design, implement, and maintain scalable data infrastructure in native AWS</li><li>Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads</li><li>Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting</li><li>Work closely with product and analytics teams to understand requirements and deliver high-performance solutions</li><li>Champion best practices for security, compliance, and governance in data infrastructure</li><li>Identify opportunities to optimize performance and cost of data platforms</li><li>Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem</li></ul> 
A day in the life 
Your primary focus will be empowering customers to succeed with their data by ensuring they can: 
<ul><li>Gather and access data at scale &ndash; Enable seamless data collection and retrieval that grows with their needs</li><li>Extract meaningful insights &ndash; Provide the right tools and capabilities to uncover the answers they're seeking</li><li>Trust their data &ndash; Maintain confidence in the completeness, accuracy, and reliability of their information</li></ul>
Achieving these goals requires close collaboration and strong partnerships with Product and Data Science teams to deliver solutions that truly meet customer needs. 
 
About the team 
Amazon Interactive Video Service (Amazon IVS) is a managed live streaming solution from AWS that enables low-latency and real-time video experiences for millions of viewers worldwide. We power engaging live experiences for some of the largest customers in the live video space and continuously push the boundaries of what&rsquo;s possible with interactive video technology.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of software development engineer or related occupational experience</li><li>1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience</li><li>1+ years of Object Oriented Design experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 165,200.00 - 223,600.00 USD annually 
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually</div>

Software Dev Engineer II, Amazon Interactive Video Service (IVS)

Vast

<div><h1 class="jobSectionHeader">Developer Experience Engineer</h1>
Vast.ai &middot; Los Angeles or San Francisco Bay Area<h3 class="jobSectionHeader">
About Us</h3>
Vast.ai&rsquo;s cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing&mdash;reshaping our future for the benefit of humanity.
We are a growing and highly motivated team dedicated to an ambitious technical plan. Our structure is flat, our ambitions are out‑sized, and leadership is earned by shipping excellence.
We seek engineers with strong intrinsic drive, a true passion for advancing the state of the art, and a mix of architecture, coding, and communication skills.
We've never had a dedicated role focused on the developers who build on Vast: the people renting compute from us to train and ship their models. That's what we're hiring for. You'll be our first DevEx Engineer, and you'll own the experience of building on Vast: the reference implementations and example code developers copy, and how we show up in the community around them.<h2 class="jobSectionHeader"> 
Why now</h2>
There's already an active community around Vast in our Discord, on Reddit, on X, and in YouTube comments. Some of it is the builders you'll serve; some of it is hosts and noise. Nobody on our side is really in there today, and our competitors staff this heavily. So part of the job is showing up for the developers who are already here, and part of it is growing the right audience around them. 
 
What you'll own<ul><li>
Technical content. Tutorials, example repos, and short videos that show people how to get something running on Vast. The useful kind that developers pass around on their own.</li><li>
Product feedback. You'll hear what's broken before anyone else does. Get it back to the product team, clearly and often.</li><li>
Events. Run our presence at hackathons (we already have sponsorships lined up), meetups, and conferences, including getting on a plane and showing up in person.</li><li>
Community. Be a real presence in our Discord, on Reddit, and on X. Answer the actual technical questions people ask, the kind they post at 1am when a container won't start. Set the tone for how Vast talks to developers.</li><li>
Creator partnerships. Work with developer-focused YouTubers and other creators, the ones with real audiences rather than bought ones.</li></ul> 
What you won't own
To be straight about scope: this role doesn't cover paid ads, brand and positioning strategy, or the growth dashboard. It's also focused on the demand side, the developers who build on Vast, not our GPU hosts and suppliers, who have their own very different needs. Other people own all of that and you'll partner with them. We want your time going into the builder community and the content that serves it, because that's where it pays off. 
 
Who you are<ul><li>
You've been an engineer. You can deploy a model and debug someone's setup, and developers can tell you've done the work yourself. This part can't be faked.</li><li>
You've built a developer community before, ideally close to from scratch. You know what makes one grow and what quietly kills it.</li><li>
You like people more than most engineers do. Writing, posting, talking, showing up at events. That's the actual day-to-day.</li><li>
You run yourself. Nobody's going to hand you a content calendar, and you'd rather ship something than sit in a planning meeting about it.</li></ul> 
Nice to have<ul><li>
Time at a cloud, GPU, AI-infrastructure, or developer-tools company.</li><li>
Something you've made that traveled: a tutorial series people reference, a repo with real stars, a talk that got passed around.</li><li>
Working knowledge of the AI/ML stack: model deployment, inference, fine-tuning.</li></ul> 
Your first 90 days<ul><li>
Get a steady, regular presence going on Reddit and Discord.</li><li>
Ship your first batch of tutorials and example repos.</li><li>
Represent Vast at a hackathon we're already sponsoring this summer.</li><li>
Give us a clear read on how other GPU and AI-infra companies show up with developers, and where we're behind.</li></ul> 
Compensation and location
$160,000&ndash;$200,000 base depending on experience, plus equity. We're profitable, venture-backed, and growing, so the equity is a stake in a real company with a real valuation, not a lottery ticket. Los Angeles or San Francisco Bay Area. Travel and conference budget covered.<h3 class="jobSectionHeader">
Benefits</h3><ul><li>
Comprehensive health, dental, vision, and life insurance</li><li>
401(k) with company match</li><li>
Meaningful early-stage equity</li><li>
Onsite meals, snacks, and close collaboration with founders/tech leaders</li><li>
Ambitious, fast-paced startup culture where initiative is rewarded</li></ul>
Compensation Range: $160K - $200K</div>

Developer Experience Engineer

Ontrac Solutions

<div><h1 class="jobSectionHeader">Overview</h1>
We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.
The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<h3 class="jobSectionHeader">GenAI Architecture &amp; Production Readiness</h3>
Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.
Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.
Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.
Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.
Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.
<h3 class="jobSectionHeader">Banking Use-Case Delivery</h3>
Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.
Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.
Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.
Troubleshoot and resolve complex issues across non-production and production environments.
Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.
Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.
<h3 class="jobSectionHeader">Governance, Risk &amp; Compliance</h3>
Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.
Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.
Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.
Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.
Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.
<h3 class="jobSectionHeader">Organizational Influence &amp; Mentorship</h3>
Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.
Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.
Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.
Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.
<h2 class="jobSectionHeader">Required Qualifications</h2>
7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.
2+ years of hands-on Python programming experience.
2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
2+ years of experience with LLMs, prompt engineering, and RAG architecture.
2+ years of experience with vector databases, semantic search, and retrieval systems.
2+ years of experience with API-driven, cloud-native architectures.
2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.
Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.
<h2 class="jobSectionHeader">Preferred Qualifications</h2>
Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.
Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.
Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.
Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.
Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.
Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.
Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.
Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.
<h2 class="jobSectionHeader">Ideal Candidate Profile</h2>
The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.
This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</div>

Principal AI Engineer

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