technical lead

Tamarind Bio

<div><h1 class="jobSectionHeader">About Tamarind Bio</h1>
We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren&rsquo;t feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
Staff Software Engineer / Technical Lead
We're hiring a Staff Software Engineer to provide technical leadership across our engineering team as we continue to scale the platform behind Tamarind.
Today, our engineering team consists primarily of early and mid-career engineers. As the complexity of our systems and customer requirements continues to grow, we're looking for someone who can help guide technical decision-making, mentor engineers, and drive architectural discussions across the organization.
This is not an engineering management role.
We're looking for a hands-on technical leader who enjoys writing code, reviewing designs, solving difficult engineering problems, and helping other engineers grow. You'll work closely with the CTO to shape technical direction while remaining deeply involved in execution.
The role spans architecture, infrastructure, product development, code reviews, technical mentorship, and engineering best practices.
What You'll Do<ul><li>
Partner with the CTO on architecture, technical planning, and major engineering initiatives</li><li>
Provide technical guidance across a team of 7-8 engineers</li><li>
Lead design reviews and architectural discussions</li><li>
Help engineers navigate complex technical challenges</li><li>
Contribute directly to the codebase across infrastructure, backend services, APIs, and product development</li><li>
Review code and provide feedback on implementation approaches</li><li>
Identify opportunities to improve reliability, scalability, performance, and developer productivity</li><li>
Support technical decision-making across new products and platform capabilities</li><li>
Work closely with customers and internal stakeholders to understand requirements and translate them into practical solutions</li><li>
Help establish engineering standards as the team continues to grow</li></ul>
Week in the Life<ul><li>
Collaborate with the CTO on technical priorities and architectural decisions</li><li>
Review designs and provide guidance on implementation approaches</li><li>
Build and operate services across infrastructure, ML systems, APIs, and customer-facing applications</li><li>
Participate in code reviews and technical discussions</li><li>
Help unblock engineers working through difficult technical problems</li><li>
Work directly with customers to understand requirements and gather feedback</li><li>
Balance hands-on engineering work with technical leadership responsibilities</li></ul>
Ideal Qualifications<ul><li>
7+ years of software engineering experience</li><li>
Experience serving as a senior technical contributor, staff engineer, principal engineer, or technical lead</li><li>
Strong software architecture and distributed systems experience</li><li>
Experience building and operating production infrastructure and cloud services</li><li>
AWS experience (EC2, S3, DynamoDB, Docker, etc.)</li><li>
Ability to mentor engineers and provide technical guidance across multiple projects</li><li>
Strong communication skills and sound engineering judgment</li><li>
Comfort operating in an early-stage startup environment</li><li>
Willingness to work onsite in San Francisco</li></ul>
Technology
Our technology sits at the intersection of DevOps, MLOps, and Computational Biology. We support workloads ranging from large-scale ML inference and model deployment to workflow orchestration across research, infrastructure, and scientific computing environments.
The role requires someone who enjoys moving between architecture, implementation, operations, and mentorship while helping a growing engineering team tackle increasingly complex technical challenges.
Compensation Range: $150K - $250K</div>

Staff Software Engineer / Technical Lead

Pinterest

<div><div>About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.</div>
What you'll do:
<ul>
<li>Be the technical lead for the forecasting team. Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale.</li>
<li>Lead the full modeling lifecycle end to end: problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability.</li>
<li>Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models.</li>
<li>Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibility role with regular VP-level exposure.</li>
<li>Drive broader time‑series impact beyond point forecasts&mdash;e.g., anomaly detection, automated root‑cause analysis, campaign/channel attribution, and early‑warning signals for business health.</li>
<li>Embed forecasting into the business. Partner with BizOps/Finance and product teams to integrate forecasts and insights into operational rhythms, executive decision-making, and strategic planning.</li>
<li>Lead and mentor. Guide the work of at least two data scientists, raising the bar on technical quality, execution, and impact through candid, continuous feedback and coaching.</li></ul> 


What we're looking for:
<ul>
<li>8+ years of combined post-graduate academic and industry experience building and shipping production time‑series/forecasting models with web‑scale data.</li>
<li>Bachelor's degree in a relevant field such as Computer Science or equivalent experience.</li>
<li>A track record of delivering adjustable, well‑calibrated, and explainable forecasting systems that informing decision-making.</li>
<li>Strong background in time‑series modeling and applied statistics/econometrics; advanced degree (MS or PhD) preferred.</li>
<li>Expertise in at least one scripting language (ideally Python).</li>
<li>Strong SQL skills (Hive/Presto/Spark SQL) and experience building reliable data pipelines/workflows (e.g., Airflow).</li>
<li>Business acumen and ownership mindset&mdash;able to simplify complex problems, connect model outputs to business levers, and prioritize for impact.</li>
<li>Excellent communication skills&mdash;able to distill complex analyses and uncertainty into concise narratives for executive audiences.</li>
<li>Proven technical leadership&mdash;success leading critical projects and materially influencing the scope and output of other contributors.</li></ul> 


Relocation Statement:
<ul>
<li>This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.</li></ul> 


In-Office Requirement Statement:
<ul>
<li>We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.</li>
<li>This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.</li></ul> 


#LI-NM4

#LI-REMOTE<div>
Our Commitment to Inclusion:
<div>
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.</div>
<div></div>
<div>By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.</div></div></div>

Staff Data Scientist, Forecasting

reddit

<div><div><div><div><div><div><div><div>Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com.</div>
</div>
</div></div></div></div></div>Team overview:

The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit's Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement.

This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.

We're a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Responsibilities:
<ul>
<li>Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.</li>
<li>Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li>Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li>Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li>Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
Candidate Profile:

The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:
<ul>
<li>People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.</li>
<li>Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.</li>
<li>Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li>Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li>Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li>Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
Required qualifications:
<ul>
<li>At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well</li>
<li>Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>4+ years of hands-on experience with TensorFlow or PyTorch.</li>
<li>Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.</li>
<li>Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.</li>
<li>Exceptional Communication &amp; Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners</li>
</ul><ul><li>Experience with Ads or Engagement Modeling is a plus.</li>
</ul>
Perks and Benefits:
<ul>
<li>100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)</li>
<li>Competitive salary and equity options</li>
<li>Comprehensive health benefits (medical, dental, vision) &amp; workplace perks (home office set up stipend etc)</li>
<li>Generous 401k matching</li>
<li>Flexible vacation policy</li>
<li>Paid parental leave (4+ months)</li>
<li>Family planning support</li>
<li>Paid volunteer time off</li>
</ul>
#LI-AS1<div> 
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</div></div>

Machine Learning Engineering Manager - Ads Engagement Modeling

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
The Experience
 
Salesforce is building the next-generation Enterprise Knowledge Graph platform to power AI-driven experiences, agentic applications, semantic search, enterprise data discovery, and intelligent decision-making across the company. The platform serves as the foundational knowledge layer connecting enterprise data, business entities, ontologies, and relationships across multiple domains.
 
 
We are seeking both a Senior Member of Technical Staff (SMTS) and a Lead Member of Technical Staff (LMTS) to join our Enterprise Knowledge Graph and AI Engineering team.
 
 
The SMTS will serve as a senior engineer and core systems developer &mdash; heavily hands-on, developing, optimizing, and scaling core knowledge graph components, semantic pipeline workflows, and AI-powered frameworks. You will partner with Lead and Principal Engineers to implement technical designs and build production-ready scalable systems that support agentic AI use cases across the enterprise.
 
 
The LMTS will serve as a hands-on technical lead, systems designer, and ontology engineer &mdash; designing, building, and scaling core knowledge graph infrastructure, semantic schemas, and AI-powered developer frameworks. You will partner closely with Principal Engineers, Product Management, Ontology experts, and Data Engineering teams to turn high-level engineering visions into production-ready scalable foundations.
 
 
Both roles will actively implement and drive AI-powered engineering tools and developer platforms that improve engineering productivity, software quality, and delivery velocity across the organization. 
 
What You'll Actually Be Doing
<ul><li>Design &amp; Implement: Build and scale Salesforce's Enterprise Knowledge Graph platform components, focusing on performance, data throughput, system reliability, high availability, and robust data integrity. (LMTS: Lead hands-on design and implementation of platform subsystems; SMTS: Write high-quality, production-grade code.)
</li><li>Graph &amp; Ontology Engineering: Develop graph data models, write complex graph queries, and construct scalable data pipelines to ingest and map structured and unstructured data to enterprise ontologies and taxonomies. (LMTS: Also design enterprise ontologies, taxonomies, semantic layers, entity resolution frameworks, graph APIs, and vector search capabilities to support advanced RAG and agentic workflows.)
</li><li>Semantic Routing: Write and maintain Python-based semantic routing frameworks to parse, classify, and dynamically direct incoming queries to the appropriate knowledge graph indexes or vector databases. (LMTS: Design, optimize, and productionize routing frameworks at enterprise scale, steering queries to appropriate knowledge graphs, ontology sub-graphs, or vector databases.)
</li><li>AI Tooling &amp; Automation: Build, integrate, and leverage AI-powered developer tools and engineering automation platforms utilizing ecosystems such as Claude, Cursor, Windsurf, AI Agents, and Model Context Protocol (MCP) frameworks. (LMTS: Also develop, deploy, and optimize these tools; drive strategy and productionization.)
</li><li>Data Integration: Build scalable data pipelines and engineering patterns to ingest, transform, and orchestrate structured, unstructured, and third-party data sources into graph-based platforms mapped tightly to enterprise ontologies.
</li><li>Feature Ownership &amp; Technical Execution: Own the technical execution of specific platform features from concept through design, coding, testing, and production deployment. (LMTS: Also translate high-level technical visions and roadmaps into concrete system blueprints, ontology schemas, and execution plans.)
</li><li>Code Quality &amp; Rigor: Participate heavily in code reviews, write comprehensive automated unit/integration tests, and ensure adherence to engineering standards and operational best practices.
</li><li>Technical Mentorship: Provide technical guidance and mentorship to engineers on the team. (SMTS: Mentor MTS and Associate engineers. LMTS: Provide day-to-day guidance, code reviews, and design direction to SMTS, MTS, and associate engineers, fostering a culture of technical rigor and operational maturity.)
</li><li>Cross-Functional Collaboration: Work closely with Lead/Principal Engineers, Product Managers, and Data Engineering teams to deliver robust features aligned with broader enterprise AI priorities. (LMTS: Also partner with PMTS engineers and Ontology governance boards to ensure alignment with AI infrastructure standards.)
</li><li>Evaluate &amp; Innovate (LMTS): Conduct deep-dive evaluations of emerging graph technologies, ontology modeling tools, semantic reasoning frameworks, vector databases, and AI tooling to continuously modernize the platform.
</li></ul>You're Our Person If...
SMTS
<ul><li>Experience: 8+ years of hands-on software engineering experience in development, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Core Programming: Expert-level coding skills in backend ecosystems, with strong fluency in Python and standard object-oriented/functional programming languages.
</li><li>Semantic Routing &amp; AI: Hands-on experience developing and deploying custom semantic routers using Python (leveraging native embeddings, LangChain, or mathematical logic like cosine similarity) alongside RAG architectures, vector search platforms, and AI workflows.
</li><li>Graph &amp; Ontology Fundamentals: Solid experience working with graph databases and semantic web concepts (e.g., Neo4j, RDF/OWL, SPARQL, property graphs) and mapping data to structured taxonomies.
</li><li>Developer Tooling: Practical experience configuring, testing, or integrating AI-assisted engineering tools or automation workflows (e.g., Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks).
</li><li>Distributed Systems &amp; Cloud: Proven experience building applications on cloud-native systems (AWS, GCP, or Azure) utilizing microservices, REST/gRPC APIs, and event-driven data streaming (e.g., Kafka).
</li><li>Delivery: Track record of owning and successfully delivering complex features in an agile, production-scale environment.
</li></ul>LMTS
<ul><li>Experience: 10+ years of hands-on experience in software engineering, data engineering, distributed systems, or enterprise data platforms.
</li><li>Education: A related technical degree required.
</li><li>Ontology &amp; Graph Expertise: Solid, hands-on experience designing and building Knowledge Graph platforms, formal ontologies, semantic models, taxonomies, or enterprise metadata management systems.
</li><li>Tooling &amp; Ecosystems: Strong hands-on experience with graph technologies and ontology engineering tools (e.g., Neo4j, TopQuadrant, Prot&eacute;g&eacute;, RDF/OWL, SPARQL, SHACL, property graphs) and semantic reasoning frameworks.
</li><li>AI &amp; Retrieval: Proven experience implementing graph-powered AI solutions, vector search platforms, Retrieval-Augmented Generation (RAG) architectures, and orchestrating agentic workflows.
</li><li>Semantic Routing Mastery: Demonstrated hands-on experience designing, optimizing, and productionizing custom semantic routers using Python (leveraging native embeddings, LangChain, semantic-router, or specialized mathematical logic like cosine similarity) to decouple intent handling from expensive LLM calls.
</li><li>Developer Automation: Experience deploying and integrating AI-assisted engineering tools or automation workflows using ecosystems like Claude, Cursor, Windsurf, GitHub Copilot, or MCP frameworks.
</li><li>Backend &amp; Cloud: Strong experience with cloud-native system designs (AWS, GCP, or Azure), distributed systems, microservices, and high-throughput event-driven systems.
</li><li>Leadership: Demonstrated experience leading feature teams, guiding technical execution, and mentoring mid-to-senior level engineers.
</li></ul>Even Better If...
SMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
</li><li>Familiarity with ontology validation frameworks (e.g., SHACL) and data quality governance.
</li><li>Experience building integrations with data platform environments like Salesforce Data Cloud or enterprise CRM metadata architectures.
</li><li>Experience optimizing low-latency applications and heavy-throughput vector search lookups.
</li><li>Passion for engineering automation and driving personal/team velocity via advanced AI development tools.
</li></ul>LMTS
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field with a focus on Semantic Web or Knowledge Representation.
</li><li>Direct experience integrating platforms with Salesforce Data Cloud, CRM platforms, or metadata-driven system designs.
</li><li>Experience with semantic routing at enterprise scale, high-throughput enterprise search systems, and graph-powered recommendation engines.
</li><li>Deep familiarity with advanced ontology governance, federated knowledge management, and data contract alignment.
</li><li>Proven track record of optimizing engineering team velocity through the tailored implementation of AI developer tooling.
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.&amp;#xa;&amp;#xa;The typical base salary range for this position is $148,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $285,800 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Data Engineer (SMTS/LMTS) - Knowledge Graph & AI

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Software Engineering
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
Applications will be accepted until 07/15/2026.
Join Salesforce's brand-new IT Employee Success and Finance Platform and Innovations team &mdash; a greenfield engineering org built from the ground up since early 2026 to define the data foundation powering HR and Finance at global scale. Based in San Francisco, CA; Indianapolis, IN; Denver, CO; New York, NY; or Atlanta, GA, you will serve as the technical authority for our Workday integration ecosystem, architecting the pipelines that make employee and financial data available, accurate, and ready for agentic use cases across Salesforce.
<h2 class="jobSectionHeader">What You'll Actually Be Doing
</h2><ul><li>Architect and govern the integration landscape between Workday and Salesforce's broader enterprise ecosystem &mdash; designing scalable, secure, high-throughput pipelines that treat PII and SOX-regulated data with zero tolerance for error.
</li><li>Translate complex HR and Finance business strategies into reusable, well-documented integration platforms that make the entire engineering organization more efficient and capable of supporting agentic workloads.
</li><li>Partner with HR and Finance business stakeholders to define data integrity standards, validate integration accuracy, and drive adoption of engineering excellence practices including modern CI/CD for SaaS and robust testing automation.
</li><li>Mentor lead and staff engineers, lead architectural review processes, and establish guardrails that raise the technical bar across the team as the platform scales.
</li></ul><h2 class="jobSectionHeader">You're Our Person If&hellip;
</h2><ul><li>You have 10 or more years of software engineering experience, including at least 2 years in a technical lead or staff capacity, with a strong track record of building SaaS-to-SaaS integrations and custom middleware/APIs bridging legacy and modern enterprise systems.
</li><li>You have deep experience handling high-stakes financial or HR data &mdash; you understand that a 1% data mismatch in Finance or HR is a 100% failure, and you architect accordingly with SOX compliance and auditability at the center.
</li><li>You think in platforms, not features &mdash; your work emphasizes reusability, documentation, and consistent engineering patterns that downstream consumers can trust.
</li><li>You are a skilled communicator who can partner with non-technical business stakeholders, influence engineering direction without direct authority, and drive alignment across cross-functional teams.
</li><li>A related technical degree required.
</li></ul><h2 class="jobSectionHeader">Even Better If&hellip;
</h2><ul><li>You have direct hands-on experience with Workday (Extend, Orchestration, Integration Studio, or similar tools).
</li><li>You have worked in a FinTech or highly regulated industry where audit trails and compliance are non-negotiable.
</li><li>You are familiar with the Salesforce ecosystem &mdash; including MuleSoft, Data Cloud, or Slack &mdash; and understand how to connect Workday data into these platforms.
</li><li>You have experience standing up new platform teams or programs from scratch, including defining standards and onboarding engineering contributors.
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.&amp;#xa;&amp;#xa;The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.&amp;#xa;&amp;#xa;The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.</div>

Lead Software Engineer, ES & Finance Platform

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act. 
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Sunnyvale, CA, USA.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Bachelor's degree or equivalent practical experience. 
</li>
<li>8 years of experience in software development. 
</li>
<li>5 years of experience testing, and launching software products. 
</li>
<li>5 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.</li>
<li>Experience integrating generative AI tools or LLM interfaces into workflows.</li>
<li>Experience in software engineering, generative AI agent, and cross-functional collaboration.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Master&rsquo;s degree or PhD in Engineering, Computer Science, or a related technical field. 
</li>
<li>8 years of experience with data structures/algorithms.</li>
<li>3 years of experience in a technical leadership role leading project teams and setting technical direction. 
</li>
<li>3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.</li>
<li>Experience with data engineering/large data set transformation and curation.</li>
<li>Experience with C++.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The Cloud Optimize team provides cost and performance optimization to Google Cloud Platform (GCP) customers. To do this we rely on a unique set of data and pipelines from other Cloud Products across GCP. You will help lead the efforts to envision these datasets, join with existing datasets, and provide the data to all first-party and third-party agents who need them. 
Optimization spans cost, performance, and capacity for projects and applications developed on GCP. Our outlook is to help developers autonomously optimize their applications for cost, performance, and capacity. We do this by developing agent skills and tooling for use with Gemini models.
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits 
 
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Provide technical leadership on high-impact projects. 
</li>
<li>Manage project priorities, deadlines, and deliverables. 
</li>
<li>Design, develop, test, deploy, maintain, and enhance large-scale software solutions. 
</li>
<li>Work with partners across GCP. Develop and launch data pipelines that feed our GCP-native AI Agents. 
</li>
<li>Develop and launch APIs and MCP servers to make our data available to first-party and third-party agents.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Staff Software Engineer, Agent-Centric Data and APIs

Encord

<div>
 
 About Us
 
 
 
 Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.
 
 
 We're an ambitious team of 100+ working at the frontier of AI and have raised $110M in funding, including a Series C backed by Wellington Management, CRV, Next47, and Y Combinator.
 
 
 
 The role
 
 
 
 We're looking for a Senior Growth Manager to architect how technical buyers find, evaluate, and choose our platform &mdash; from first signal to closed deal. You'll own our demand generation strategy, building pipeline from target accounts within a defined vertical, deepening engagement with existing customers, and operating as a true partner to Sales. You'll lead a squad of three, setting direction, developing your team, and ensuring output connects directly to revenue.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Lead and develop your team &mdash; setting clear priorities, unblocking people, and maintaining a high bar for output across all growth programs
 </li>
 <li>
 Own pipeline strategy for target enterprise accounts &mdash; coordinating content, campaigns, outreach, and in-person touchpoints to drive qualified opportunities in partnership with Sales and SDRs
 </li>
 <li>
 Deploy AI agents to monitor account-level signals, identifying when target accounts are moving from cold to warm and surfacing the right moment for Sales to engage
 </li>
 <li>
 Use AI-driven intent tools at the contact level to flag high-intent prospects, inform personalisation, and help Sales prioritise outreach across an account
 </li>
 <li>
 Build and own our conference and field event strategy &mdash; identifying the right moments in the ML Ops, Data Ops, and AI infrastructure calendar, activating target accounts before and after events, and converting in-person presence into pipeline
 </li>
 <li>
 Develop co-marketing programs with technology partners across the ML Ops and AI infrastructure ecosystem, turning integrations and shared customers into joint campaigns and warm introductions into target accounts
 </li>
 <li>
 Work closely with AEs and Sales leadership to ensure Sales receives well-qualified, well-timed opportunities
 </li>
 <li>
 Manage lead routing, enrichment, and nurture tracks to reduce friction across enterprise buyer journeys
 
 
 </li>
 </ul>
 
 Who we're looking for
 
 
 
 <ul>
 <li>
 You're structured and precise in how you think about markets &mdash; you know how to map a landscape, identify where to focus, and build programs that convert that focus into pipeline
 </li>
 <li>
 You're energised by in-person relationship building &mdash; conferences, roundtables, and industry events are where you do some of your best work
 </li>
 <li>
 You're quick to pick up new tools and workflows &mdash; you're already using AI to work faster and smarter, and you're curious about where it goes next
 </li>
 <li>
 You can engage credibly on technical topics &mdash; ML infrastructure, compute orchestration, model evaluation, and developer tooling are areas you're motivated to go deep on
 </li>
 <li>
 You've managed or led small teams and know how to get the best out of people while keeping programs moving
 
 
 </li>
 </ul>
 
 Experience requirements
 
 
 
 <ul>
 <li>
 3+ years in B2B growth, strategy, finance, or a commercially rigorous field &mdash; with a track record of owning outcomes, not just workstreams
 </li>
 <li>
 Direct experience in or exposure to the ML Ops, Data Ops, or AI infrastructure space, or adjacent areas such as model evaluation, robotics, physical AI, or autonomy
 </li>
 <li>
 Experience building and executing demand generation, field event, or co-marketing programs in a B2B environment
 </li>
 <li>
 Familiarity with AI-driven intent and signal tools (e.g. 6sense, Bombora, Clay) and how they integrate into a GTM motion
 
 
 </li>
 </ul>
 
 Why Encord
 
 
 
 <ul>
 <li>
 Competitive salary, commission, and equity in a high-growth start-up
 </li>
 <li>
 Strong in-person culture - most of the team works from our London office 4+ days/week
 </li>
 <li>
 25 days annual leave + UK public holidays
 </li>
 <li>
 Annual learning &amp; development budget
 </li>
 <li>
 Travel for customer visits, events, and conferences across the UK and Europe
 </li>
 <li>
 Company lunches twice a week
 </li>
 <li>
 Monthly socials &amp; bi-annual team offsites
 
 
 </li>
 </ul>
</div>

Senior Growth Manager

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