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Foundational AI Research Scientist - FAIR

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities.<br>
<br>
As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.<br>
<br>
Key job responsibilities<br>
<ul><li>Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI</li><li>Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results</li><li>Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems</li><li>Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>PhD in computer science, machine learning, engineering, or related fields</li><li>Experience or publications related to Agentic AI applications</li><li>Programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch</li><li>Excellent problem-solving skills, with the ability to think creatively and critically about complex problems</li><li>Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams</li><li>Experience with patents or publications at top-tier peer-reviewed conferences or journals</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>
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.<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, AGI

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is transforming advertising through generative AI technologies. We help millions of customers discover products and engage with brands across Amazon.com and beyond. Our team combines human creativity with artificial intelligence to reinvent the entire advertising lifecycle&mdash;from ad creation and optimization to performance analysis and customer insights.<br>
<br>
We develop responsible AI technologies that balance advertiser needs, enhance shopping experiences, and strengthen the marketplace. Our team values innovation and tackles complex challenges that push the boundaries of what's possible with AI.<br>
<br>
Join us in shaping the future of advertising.<br>
<br>
Key job responsibilities<br>
This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include:<br>
<br>
<ul><li>Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences.</li><li>Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions.</li><li>Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts.</li><li>Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor junior scientists and engineers to build a high-performing, collaborative team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Demonstrated expertise in Generative AI technologies, including foundation models, LLMs, and model customization for specific business applications</li><li>Hands-on experience building ads ranking, retrieval, recommendation, or personalization systems that operate at web scale</li><li>Technical proficiency in advanced AI approaches such as multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF)</li><li>Track record of designing and implementing online experimentation frameworks, including A/B testing methodologies and performance metrics for advertising or e-commerce</li><li>Proven ability to translate complex technical concepts into clear explanations for diverse audiences, from engineers to executives</li><li>Deep knowledge of computational advertising fundamentals, including auction mechanisms, advertising economics, and advertiser success metrics</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 $150,400/year in our lowest geographic market up to $260,000/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>

Senior Applied Scientist, Off-Search, Sponsored Products and Brands

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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. 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 Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:<br>
<br>
<ul><li>Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.</li><li>Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.</li><li>Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.</li><li>Contribute to the enhancement of team&rsquo;s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 8+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li><li>Experience developing and deploying models in real-world production environments.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.</li><li>Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.</li><li>Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).</li><li>Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.</li><li>Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.</li><li>Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.</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 $150,400/year in our lowest geographic market up to $260,000/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>

Sr. Applied Scientist, Sponsored Products and Brands Off-Search

<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

Waypoint Bio

<div>
 <p>
  <strong>
   Scientist / Senior Scientist, Molecular and Cellular Biology
  </strong>
 </p>
 <ul>
  <li>
   Full-time position
  </li>
  <li>
   Competitive compensation (Salary, Benefits &amp; Options)
  </li>
  <li>
   430 E 29th Street, New York
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Waypoint Bio
  </strong>
  is a biotech startup building the next generation of cell therapies for solid tumors. Traditional cell therapy preclinical development faces a trade-off between
  <em>
   in vitro
  </em>
  approaches that are fast but inaccurate, and
  <em>
   in vivo
  </em>
  approaches that are accurate but slow and expensive. Using our proprietary platform combining spatial biology, pooled screening,
  <em>
   in silico
  </em>
  protein engineering, and machine learning, we can obtain both depth and breadth when screening cell therapy candidates &ndash; speed without compromising on
  <em>
   in vivo
  </em>
  accuracy. Our team is highly collaborative, interdisciplinary, and shares the mission of developing novel immune cell therapies to benefit patients' lives.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Position Summary:
  </strong>
 </p>
 <p>
  We are seeking a highly motivated, creative scientist who thrives in a fast-paced and collaborative environment. The ideal candidate will have extensive expertise in synthetic biology, molecular, and cell biology and will contribute to projects spanning genetic engineering, cell-based assays, and pooled screening. Their primary tasks will be to apply their knowledge of molecular and cell biology to design novel T cell therapies, manufacture these cell therapies, and test their function using cell-based assays. Top candidates will also have deep knowledge of synthetic biology, immunology, or cell therapy, and will be able to apply this to Waypoint&rsquo;s spatial pooled screening technology in a variety of
  <em>
   in vitro
  </em>
  systems. At Waypoint, you will work collaboratively with our team of computational and wet-lab scientists to develop new therapeutic options to treat solid tumors.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Duties and Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, execute, and troubleshoot molecular biology workflows involved in cell therapy design/testing, including cloning and genome engineering.
  </li>
  <li>
   Develop, optimize, and run cell-based assays, contributing to pipeline programs and platform development .
  </li>
  <li>
   Engineer and characterize cell therapies and synthetic biology constructs using cutting-edge tools and assays.
  </li>
  <li>
   Contribute to high-throughput screening approaches, including pooled or arrayed formats, for discovery and validation efforts.
  </li>
  <li>
   Develop and evaluate delivery strategies for genetic cargo across diverse biological systems.
  </li>
  <li>
   Actively engage in prioritizing key milestones and developing appropriate timelines.
  </li>
  <li>
   Provide conceptual input on in vivo experimental design and interpretation in a team setting.
  </li>
  <li>
   Keep detailed scientific records in an electronic lab notebook and actively contribute towards the organization of the lab.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications
  </strong>
 </p>
 <p>
  <em>
   While prior T cell experience is preferred, we also encourage applications from candidates with strong molecular biology experience in non-mammalian systems (e.g. non-mammalian model organisms).
  </em>
 </p>
 <ul>
  <li>
   Ph.D. in Molecular Biology, Cell Biology, Immunology, or Cancer Biology, or a related field. Alternatively, Bachelor&rsquo;s degree or Master&rsquo;s degree with 6 years or 4 years of relevant experience, respectively.
  </li>
  <li>
   High degree of expertise in molecular biology (e.g. Gibson cloning), genetic manipulations (e.g. CRISPR, lentivirus, etc.), RNA/DNA purification, and preparation of NGS libraries.
  </li>
  <li>
   An excellent scientific track record with published papers or recent experience in the field of molecular biology, genomics, cell biology, immunology, or related fields.
  </li>
  <li>
   Superb organizational abilities and precise scientific record keeping in electronic lab notebooks.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Experience culturing T cells
   <em>
    ex vivo
   </em>
   and using these cells for downstream assays.
  </li>
  <li>
   Practical knowledge of the immune cell therapy field, with a focus on T cell therapy.
  </li>
  <li>
   Knowledge of the interplay between the immune system and the tumor microenvironment.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Send CV and cover letter to apply:
  </strong>
 </p>
 <p>
  jobs@waypointbio.com
 </p>
</div>


Scientist / Senior Scientist, Molecular and Cellular Biology

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div>We are seeking a highly skilled Senior Machine Learning Engineer with expertise in Databricks to join our innovative team. The ideal candidate will be responsible for developing, fine-tuning, and managing machine learning models in a production environment while optimizing costs and performance on the Databricks platform.</div><div><br>
</div><div></div><br>
<ul><li>Develop and implement end-to-end machine learning solutions using Databricks, leveraging its Unified Analytics Platform
</li></ul><ul><li>Fine-tune and optimize machine learning models deployed in production environments
</li></ul><ul><li>Set up and manage automation processes for model training, evaluation, and deployment on Databricks
</li></ul><ul><li>Optimize Databricks cluster configurations and resource utilization to manage overall platform costs efficiently
</li></ul><ul><li>Collaborate with cross-functional teams to integrate ML solutions into existing products and workflows
</li></ul><ul><li>Implement best practices for version control, testing, and documentation of ML models and pipelines
</li></ul><ul><li>Monitor and analyze model performance, making data-driven decisions for continuous improvement</li></ul><br>
<div><br>
</div><div>Roles &amp; Responsibilities
</div><ul><li>Develop and implement end-to-end machine learning solutions using Databricks, leveraging its Unified Analytics Platform
</li></ul><ul><li>Fine-tune and optimize machine learning models deployed in production environments
</li></ul><ul><li>Set up and manage automation processes for model training, evaluation, and deployment on Databricks
</li></ul><ul><li>Optimize Databricks cluster configurations and resource utilization to manage overall platform costs efficiently
</li></ul><ul><li>Collaborate with cross-functional teams to integrate ML solutions into existing products and workflows
</li></ul><ul><li>Implement best practices for version control, testing, and documentation of ML models and pipelines
</li></ul><ul><li>Monitor and analyze model performance, making data-driven decisions for continuous improvement
</li></ul><ul><li>Stay current with the latest advancements in machine learning and Databricks technologies
</li></ul>
<div></div><div>Salary Range-$110,000-$130,000 a year
</div>
<div><p>#LI-NR3</p>
<p><b>TCS Employee Benefits Summary:</b></p><br>
<p></p>
<ul><li>Discretionary Annual Incentive.</li>
<li>Comprehensive Medical Coverage: Medical &amp; Health, Dental &amp; Vision, Disability Planning &amp; Insurance, Pet Insurance Plans.</li>
<li>Family Support: Maternal &amp; Parental Leaves.</li>
<li>Insurance Options: Auto &amp; Home Insurance, Identity Theft Protection.</li>
<li>Convenience &amp; Professional Growth: Commuter Benefits &amp; Certification &amp; Training Reimbursement.</li>
<li>Time Off: Vacation, Time Off, Sick Leave &amp; Holidays.</li>
</ul>Legal &amp; Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing
</div></div></div></div><div><div><div><b>Location</b></div>
<div>New York, NY</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Engineer</div>
</div><div><div><b>Job Id</b></div>
<div>385812</div>
</div><div><div><b>Desired Skills</b></div>
<div>DevOps</div>
</div><div><div><b>Salary Range</b></div>
<div>$110,000-$130,000 a year</div></div></div></div><div></div>

Engineer

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