ml engineer

Norm AI

<div><p><b>About Norm Ai</b></p><p>
Norm Ai, the leading Legal &amp; Compliance AI company, has a client base with a combined $30 trillion in assets under management. By turning legal code into AI code, Norm enables enterprises to move faster and more comprehensively in their legal and compliance processes with reliability and trust.</p><p></p><p>
Norm&rsquo;s platform combines frontier AI, proprietary legal reasoning systems, and embedded legal and regulatory expertise.</p><p></p><p>
We have recently raised more than $140 million, backed by Blackstone, Bain Capital, Vanguard, Citi, New York Life, TIAA, Coatue, Craft Ventures, Henry R. Kravis (KKR co-founder), and Marc Benioff (Salesforce CEO).</p><p></p><p>
Norm Ai pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain-specific AI agents with Norm&rsquo;s proprietary suite of no-code software tools. We hired dozens of lawyers from premier U.S. law firms and trained them as Legal Engineers, who specialize in Large Language Model powered legal workflows.</p><p></p><p>
Norm Ai technology is deployed inside many of the largest and most consequential institutions in the world. The company is growing quickly and hiring across all teams.</p><p></p><p><b>
About Norm Law</b></p><p>
Norm Law is the first AI-native full-service law firm for global institutional clients like Blackstone (see recent coverage of our Blackstone partnership. Legal Engineering, a discipline pioneered by Norm Ai, where lawyers develop legal AI agents, powers Norm Law to deliver faster, more precise, and more consistent legal services. With purpose-built AI agents completing first passes of work, Norm lawyers supervise, review, and focus on what matters most: strategic judgment and expert advice.</p><p></p><p>
Norm Law and Norm Ai, together, are building Legal AGI.</p><p></p><p><b>
This Role</b></p><p>
As a Founding AI Engineer, you will work side-by-side with partners and associates. You&rsquo;ll build fast prototypes, test them directly in live workflows, and push successful systems into our platform. The role blends full stack engineering, AI, and data science. It requires fluency in production codebases, speed in iteration, and depth in applying LLMs to solve real problems.</p><p></p><p>
This is a hands-on role at the intersection of AI, reasoning, and high-stakes decision-making. You&rsquo;ll work embedded with domain experts (e.g., lawyers, analysts, compliance officers) to observe workflows, identify inefficiencies, and prototype AI systems that transform how expert reasoning is performed.</p><p></p><p><b>
Skills &amp; Experience</b></p><ul><li><p>
4+ years of experience as a software engineer, ML engineer, or data scientist</p></li><li><p>
Strong programming skills in Python, proficiency in Docker and data storage technologies such as Postgres and Redis</p></li><li><p>
Willingness to work with frontend technologies (Typescript, React, etc.) to bridge the gap between research ideas and the productization of new initiatives</p></li><li><p>
Experience in AI/ML infrastructure and tooling</p></li><li><p>
Interest in becoming a legal and compliance domain expert and working closely with professionals in the field</p></li><li><p>
Strong reading, writing, and quantitative skills, as well as a data-driven approach to problem solving</p></li></ul><p></p><h3 class="jobSectionHeader"><b>
Skills &amp; Experience - Pluses</b></h3><ul><li><p>
Previously built one off analytical systems in trading, research, or other data-heavy fields.</p></li><li><p>
Interest in working directly with non-technical experts to translate their logic into code.</p></li><li><p>
Familiarity with and an eagerness to apply the latest AI research</p></li><li><p>
Experience applying traditional ML systems and processes in the context of state-of-the-art LLMs</p></li><li><p>
Experience deriving insights from PDFs and other unstructured or semi-structured data types</p></li><li><p>
Experience with context engineering and memory in the context of AI agents</p></li><li><p>
Experience modeling uncertainty in ML systems</p></li></ul><p></p><p><b>
Comp &amp; Benefits</b></p><p><i>
$220,000-$285,000 base + employee equity (level dependent)</i></p><p></p><p>
The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills (as uncovered during the interview process), experience, and relevant education or training. Please note that the compensation details listed here reflect the base salary only, and do not include equity or benefits. We offer a competitive salary along with equity compensation. Our comprehensive benefits package includes a 401(k) plan with an employer match. Employees enjoy top-tier insurance coverage, encompassing health, dental, hospital, accident, and vision plans.</p><p></p><p>
We embrace a flexible hybrid model, typically in-office 4-5 days per week. For candidates needing to relocate to NYC, we provide relocation reimbursement. You'll thrive in our fast-paced learning environment where professional growth is constant.</p><p></p><p><i>
If you&rsquo;re interested in the role but aren&rsquo;t sure whether you&rsquo;re a good fit, we&rsquo;d still like to hear from you.</i></p><p>
To learn more about Norm Ai, visit our <b>website</b>.</p></div>

Founding AI Engineer - Norm Law

Cognizant Technology Solutions

<div><p>At Cognizant, our global community sets us apart&mdash;an energetic, collaborative and inclusive workplace where everyone can thrive. And with projects at the forefront of innovation, you can build a varied, rewarding career and draw inspiration from dedicated colleagues and leaders. Cognizant is right where you belong. If you meet our background requirements and skills and are looking for an opportunity with these skills and expertise, here is the ideal opportunity for you!</p><p>
Cognizant Technology Solutions is looking for a AGENTIC AI DEVELOPER to join our dynamic team. Collaborate with cross-functional teams to drive innovation and deliver impactful solutions that align with our company&rsquo;s goals.</p><p></p><p><b>
Role:</b> AGENTIC AI DEVELOPER</p><p>
Applications will be accepted until Dec 31, 2025</p><p></p><p><b>
Location: </b>Candidates will need to work out of the Client&rsquo;s office in NJ/NY or Dallas, TX. This is a completely Remote role for candidates based in rest of US.</p><p></p><p><b>
About this Team and Role</b></p><p></p><p>
In this role, you will be responsible for launching and implementing GenAI agentic solutions aimed at reducing the risk and cost of managing large-scale production environments with varying complexities. You will address various production runtime challenges by developing agentic AI solutions that can diagnose, reason, and take actions in production environments to improve productivity and address issues related to production support.</p><p><b>
</b></p><p><b>What you&rsquo;ll do:</b></p><p></p><ul><li>Build agentic AI systems: Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access.</li><li>Productionize LLMs: Build evaluation framework for open-source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations.</li><li>Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.</li><li>Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business-aligned outcomes.</li><li>Safety, reliability, and governance: Build validator models, adversarial prompts, and policy checks into the stack; enforce deterministic fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk.</li><li>Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.</li><li>Build a RAG pipeline: Curate domain-knowledge; build data-quality validation framework; establish feedback loops and milestone framework maintain knowledge freshness.</li><li>Raise the bar: Drive design reviews, experiment rigor, and high-quality engineering practices; mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns</li><li>Role Requirements: understand what skills, experience, and qualities you are looking for.</li></ul><p></p><p><b>
ESSENTIAL SKILLS</b></p><p><b>
</b></p><ul><li>5+ years of software development in one or more languages (Python, C/C++, Go, Java); strong hands-on experience building and maintaining large-scale Python applications preferred.</li><li>3+ years designing, architecting, testing, and launching production ML systems, including model deployment/serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.</li><li>Practical experience with Large Language Models (LLMs): API integration, prompt engineering, fine-tuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).</li><li>Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).</li><li>Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.</li><li>Strong analytical problem-solving, ownership, and urgency; ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.</li><li>Preferred: Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation).</li></ul><p></p><p><b>
Competencies:</b></p><ul><li>Ownership and Accountability</li><li>Autonomy</li><li>High Level of Integrity</li><li>Clear Communication</li><li>Creative Problem Solver</li></ul><p></p><p><b>
Salary and Other Compensation:</b></p><p>
The annual salary for the position depends on experience and other qualifications of the successful candidate and is between $95,000/year - $130,000/year. This position is also eligible for Cognizant&rsquo;s discretionary annual incentive program, based on performance and subject to the terms of Cognizant&rsquo;s applicable plans.</p><p></p><p><b>
Work Authorization:</b><br>
Cognizant will only consider applicants for this position who are legally authorized to work in the United States without company sponsorship</p><p>
</p><p><b>Benefits</b>: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:</p><ul><li><p>
Medical/Dental/Vision/Life Insurance</p></li><li><p>
Paid holidays plus Paid Time Off</p></li><li><p>
401(k) plan and contributions</p></li><li><p>
Long-term/Short-term Disability</p></li><li><p>
Paid Parental Leave</p></li><li><p>
Employee Stock Purchase Plan</p></li></ul><p>
#LI-SA1</p><p><b>
Disclaimer: </b>The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law</p></div>

Senior Agentic AI Developer

Scale AI

<div></div><div><div><div>Equal opportunity employer</div></div><div></div><div><div>
Remote-friendly culture</div></div><div></div><div><div>
Competitive benefits package</div></div></div>
<br><div><p>The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers.</p>
<div>
Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.</div>
<h3 class="jobSectionHeader"><b>
You will:</b></h3>
<ul><li>Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.</li>
<li>Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics</li>
<li>Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines</li>
<li>Work with massive datasets to develop both generic models as well as fine tune models for specific products</li>
<li>Build scalable machine learning infrastructure to automate and optimize our ML services</li>
<li>Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations</li>
<li>Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment</li>
<li><b>This role will require an active security clearance or the ability to obtain a security clearance.</b></li>
</ul><h3 class="jobSectionHeader"><b>Ideally You&rsquo;d Have:</b></h3>
<ul><li>Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment</li>
<li>Solid background in algorithms, data structures, and object-oriented programming</li>
<li>Strong programing skills in Python, experience in Tensorflow or PyTorch</li>
</ul><h3 class="jobSectionHeader"><b>Nice to Haves:</b></h3>
<ul><li>Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization</li>
<li>Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments</li>
<li>Experience with computer vision, generative AI models, large language models, or agentic systems</li>
<li>Familiarity with ML evaluation frameworks and agentic model design</li>
</ul><div><div><div><div><i>
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You&rsquo;ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.</i></div></div><div>
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:</div><div>
$208,000&mdash;$300,000 USD</div></div><div><div>
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of Washington DC, Texas, Colorado is:</div><div>
$187,000&mdash;$270,000 USD</div></div></div><div><div><b><i>
PLEASE NOTE: </i></b><i>Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.</i></div>
<div><b>
About Us:</b></div>
<div><i>
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.</i></div>
<div><i>
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.</i></div>
<div><i>
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's </i><i>Know Your Rights poster</i><i> for additional information.</i></div>
<div><i>
We comply with the United States Department of Labor's </i><i>Pay Transparency provision</i><i>.</i></div>
<div><b><i>
PLEASE NOTE: </i></b><i>We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants&rsquo; needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our </i><i>privacy policy</i><i> for additional information.</i></div></div></div>

Machine Learning Engineer, Public Sector

Morgan Stanley

<div><p>Morgan Stanley Services Group, Inc. seeks a Director, Lead Data &amp; Analytics Engineer in New York, New York
</p><p></p><p>Maintain and support services and capabilities of the firm&rsquo;s internal search infrastructure. Onboard and index new data sources, clean existing index, improve relevancy algorithms, and apply AIML models to search application. Create data pipelines and ETL processes to facilitate onboarding client data into firm databases. Upgrade software system capabilities to best serve the business needs of end users. Incorporate industry best practices to improve performance and productivity of the firm&rsquo;s internal search infrastructure. Develop a monitoring mechanism for search infrastructure. Streamline and improve product delivery metrics. Troubleshoot technical issues, perform root cause analysis, and take appropriate action to remediate issues related to discovery, relevancy and data mining.
</p><p></p><p>Salary :
</p><p>Expected base pay rates for the role will be between $160,000 and $165,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
</p><p></p><p>Requirements:
</p><p></p><p>Requires a Master's degree in Computer Science, Computer Engineering, or a related field plus three (3) years of experience in the position offered or three (3) years of experience as an AI/ML Engineer, Data Scientist, or related occupation. Two (2) years of experience with: Java.
<br>
<br>
One (1) year of experience with: vended or open-source search engines; Javascript; and Python.
<br>
<br>
Any amount of experience with: building and training machine learning models; deploying machine learning models in production; AI chatbot development; Semantic search; Lucidworks Fusion connector configurations; indexing strategies for structured and unstructured data; faceted search; typeahead; relevance boosting; DevOPs; KPI&rsquo;s; Agile practices; Enterprise Git; GitHub; Jenkins; continuous integration tools, including Artifactory ro, SonarQube, selenium, and Jmeter; load testing; troubleshooting and production support; Docker; Kubernetes; and Azure.
</p><p></p><p>Qualified Applicants: To apply, visit us at https://morganstanley.eightfold.ai/careers?source=mscom and enter JR025360 in the search field. No calls please. EOE
</p><p></p><p><b>WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
</b></p><p></p><p>We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren&rsquo;t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you&rsquo;ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There&rsquo;s also ample opportunity to move about the business for those who show passion and grit in their work.
</p><p></p><p>To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-officesinto your browser.
</p><p></p><p>Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
</p><p></p><p>It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
</p><p></p><p>Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).</p></div><p></p>

Director, Lead Data & Analytics Engineer

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale.
<br>
<br>
You will work backwards from the needs of advertisers&mdash;delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production.<br>
<br>
Key job responsibilities<br>
<ul><li>Design and build agents for our autonomous campaigns experience.</li><li>Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).</li><li>Curate datasets and tools for MCP.
</li><li>Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.</li><li>Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning.</li><li>Prototype and iterate on multi-agent orchestration frameworks and workflows.</li><li>Collaborate with peers across engineering and product to bring scientific innovations into production.</li><li>Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.</li></ul><br>
About the team<br>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.<br>
<br>
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
The Autonomous Campaigns team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon&rsquo;s retail ecosystem.<br>
<br>
Our vision is to build a highly personalized, context-aware campaign creation and management system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities&mdash;from high-level product guidance down to granular keyword recommendations&mdash;and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in designing experiments and statistical analysis of results</li><li>Experience with AI/ML technologies</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in professional software development</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist II, Sponsored Products Autonomous Campaigns

hackajob

<div>
 <p>
  🔥
  <strong>
   We&rsquo;re hiring &mdash; Full Stack Software Engineer (NYC or SF)
  </strong>
 </p>
 <p>
  Chalk is building the data platform powering the next generation of ML applications. After raising a $50M Series A led by Felicis, we&rsquo;re expanding our engineering team in New York and San Francisco. This is an early-employee role &mdash; high ownership, close partnership with the co-founders, and tons of impact.
 </p>
 <p>
  <br/>
 </p>
 <p>
  What you&rsquo;ll do:
 </p>
 <ul>
  <li>
   Build product-facing features across
   <strong>
    CLI and web
   </strong>
   , focusing on developer UX.
  </li>
  <li>
   Write TypeScript, Python, Go, and React to productionize our core platform.
  </li>
  <li>
   Tackle systems problems inspired by
   <strong>
    compilers, query planners, and distributed systems
   </strong>
   .
  </li>
  <li>
   Iterate rapidly with customer feedback to deliver real results.
  </li>
 </ul>
 <li>
 </li>
 <p>
  You should have:
 </p>
 <ul>
  <li>
   2+ years professional software engineering experience
  </li>
  <li>
   Strong computer science fundamentals and real-world systems experience
  </li>
  <li>
   A track record of building polished user-facing applications
  </li>
  <li>
   Ability to work onsite Monday&ndash;Friday in
   <strong>
    NYC
   </strong>
   or
   <strong>
    SF
   </strong>
  </li>
 </ul>
 <li>
 </li>
 <p>
  Nice-to-haves: data infra, developer tools, ML/data analytics, Go.
 </p>
 <p>
  Why Chalk? Great benefits, daily lunch &amp; dinner in-office, commuter perks, strong equity upside &mdash; and the chance to help shape a platform used for mission-critical ML applications.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Questions? DM me &mdash; happy to chat! 🙌
 </p>
 <p>
  #hashtags: #hiring #fullstackengineer #startuplife #mlplatform #nyc #sanfrancisco
 </p>
</div>


Software Engineer

Uber

<div><b>About the Role</b>
<br>
<br>
We are seeking a talented and experienced Sr Software Engineer to join our Threat Defense and Response team and help drive the next generation of AI-powered cyber defense capabilities. This role will focus on advancing our ability to identify, research, investigate, and respond to evolving threats across cyber defense.<br>
<br>
As cyber threats grow in speed and sophistication, this role will be instrumental in architecting and scaling security solutions that combine advanced engineering with AI. You will collaborate with cross-functional engineering, ML, and security teams, build automation that amplifies human defenders, and shape Uber's cyber defense strategy.<br>
<br>
<b>What the Candidate Will Need / Bonus Points</b>
- What the Candidate Will Do -<br>
<ul><li>
Design and develop scalable, reliable, and high-performance software platform and services for Uber's cyber defense
</li><li>Drive development of AI agents that support cyber defense workflows including threat intelligence, hunting, research, and more.</li><li>
Collaborate with cross-functional cybersecurity experts to translate requirements into automated, production-ready capabilities.</li><li>
Collaborate with cross-functional software engineering teams to build end-to-end cyber defense solutions.</li><li>
Contribute to strategy by defining what good&quot; looks like across cyber defense domains and guiding the team toward measurable outcomes.</li><li>
Deliver high-quality, secure code and mentor junior engineers in engineering best practices.</li></ul><br>
- Basic Qualifications -<br>
<ul><li>
Bachelor's degree in Computer Science, Engineering, Cybersecurity, or a related technical field</li><li>
5+ years of experience in software engineering, with a focus on building and scaling systems</li><li>
Proficiency in at least one of the following programming languages: C++, Java, Go, or Python</li><li>
Strong experience in backend software architecture design</li><li>
Experience in building and evaluating AI agents/agentic workflows end-to-end</li><li>
Hands-on experience with cloud environments (AWS, GCP, or Azure) and containerized platforms (Docker, Kubernetes)</li></ul><br>
- Preferred Qualifications -<br>
<ul><li>
Master's or PhD degree in Computer Science, Engineering, Cybersecurity, or a related field
</li><li>Experience with AI/ML technologies and frameworks and incorporating them into production systems</li><li>
Knowledge of cybersecurity concepts, principles, tools, and best practices. Hands-on experience in a cybersecurity domain (e.g. threat intelligence, threat hunting, threat modeling, vulnerability management, detection engineering, incident response) would be a plus</li><li>
Proven track record of leading complex software projects from inception to delivery</li><li>
Strong problem-solving skills and a passion for innovation</li></ul><br>
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For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.</div>

Sr Software Engineer, AI and Backend

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