data pipeline engineer

Nautilus Bio

<div><div>Location<div>
Seattle</div></div><div>
Employment Type<div>
Full time</div></div><div>
Location Type<div>
Hybrid</div></div><div>
Department<div>
Software &amp; Bioinformatics</div></div><div>
Compensation<ul><div>
$164K &ndash; $221K &bull; Offers Equity</div></ul><div><div>
The hiring pay range for this position is based on skills, education, and experience relevant to the role. New hires are typically hired into the low to midpoint of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. Pay ranges are adjusted based on cost of labor in each respective geographical market. Your recruiter can share more about the specific pay range for your location during the hiring process.</div><div></div><div>
Benefits include medical, vision, and dental insurance, group and supplemental life insurance, 401k retirement plan, responsible paid time off, parental leave, and more. Other components of total compensation include a competitive options grant at the time of hire (with potential for additional grants).</div></div></div></div>
 <div><div><div>At Nautilus, we have a big and important mission: improve the health of millions by unleashing the potential of the proteome to accelerate drug development and enable a new world of precision and personalized medicine. We are developing a single-molecule protein analysis platform of unprecedented sensitivity, scale, and ease of use that we believe will democratize access to the proteome - one of the most dynamic and valuable sources of biological insight. To accomplish this, we are pursuing hard scientific problems with an entrepreneurial mindset and creating a world-class team of builders, innovators, and dreamers across a wide range of disciplines.</div>
We are hiring a Senior Software Engineer II to join our Cloud Data Pipeline team. This team is responsible for the data infrastructure that transforms raw protein measurement data into the scientific outputs that our customers and internal researchers depend on. You'll own ETL pipelines, cloud infrastructure, and the APIs and databases that connect our data platform to the rest of the company. As Nautilus moves into commercial deployment, this role sits at the intersection of data engineering rigor and the practical demands of a production scientific platform. Your work will directly shape what our customers can learn from their experiments and how reliably they can trust the results.
This position will report to the Manager, Data Engineering and Cloud Pipelines and is located in Seattle, WA. The position is hybrid and requires a minimum of three days onsite.
Responsibilities<ul><li><div>
Design and implement data pipelines and ETLs that process protein measurement data at scale, turning instrument outputs into reliable, query-able scientific results.</div></li></ul><ul><li>
Improve the architecture of existing cloud systems: identify structural weaknesses, propose better approaches, and drive implementation alongside the technical lead.</li></ul><ul><li>
Maintain and evolve the APIs and database schemas that serve internal teams including bioinformatics, science, and product development, adapting as their needs grow.</li></ul><ul><li>
Contribute to the team's DevOps practice: optimize AWS costs, manage cloud deployments, improve system security, and drive performance improvements through infrastructure changes.</li></ul><ul><li>
Work cross-functionally with scientific and software teams to define data quality metrics, understand how downstream consumers use pipeline outputs, and ensure the platform meets their needs.</li></ul><ul><li>
Surface and advocate for changes to project priorities and architecture across the cloud pipeline and adjacent projects.</li></ul>
Requirements<ul><li><div>
7+ years of relevant experience in a software engineering organization, with a strong track record of delivering production-quality systems.</div></li></ul><ul><li>
Bachelor's degree in Computer Science or a related field, or equivalent practical experience.</li></ul><ul><li>
Fluency in a variety of programming languages. We are currently invested in Python for our data pipelines.</li></ul><ul><li>
Solid experience with cloud infrastructure on AWS including cost management and deployment practices.</li></ul><ul><li>
Experience with CI/CD pipelines and infrastructure-as-code (e.g., Terraform, CDK).</li></ul><ul><li>
Experience with relational and non-relational database design</li></ul><ul><li>
Demonstrated experience building and maintaining data pipelines or ETL systems at production scale.</li></ul><ul><li>
Skilled in multiple technology domains with the ability to independently pick up new ones as needed.</li></ul><ul><li>
Strong communication skills and comfort working across engineering, science, and product stakeholders.</li></ul><ul><li>
Ability to identify when a change in direction is necessary and deal competently with that shift.</li></ul><ul><li>
Familiar with AI-driven development tools and methodologies.</li></ul>
Nice to Haves<ul><li><div>
Experience with Docker and container orchestration tools (Kubernetes, ECS).</div></li></ul><ul><li>
Experience with workflow orchestration tools (e.g., Nextflow, Step Functions, Airflow, Prefect).</li></ul><ul><li>
Experience with data observability, pipeline monitoring, or data quality frameworks.</li></ul><ul><li>
Background in biotech, life sciences, or scientific data processing.</li></ul><ul><li>
Familiarity with NoSQL data stores and when to use them alongside relational databases.</li></ul></div></div>

Senior Software Engineer II, Cloud Data Pipeline Seattle

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.
<h3 class="jobSectionHeader">About the Role
</h3>We are seeking a highly skilled and motivated Data Engineer to join our Growth &amp; Retention Intelligence team. In this role, you will design, build, and scale the data that power our machine learning ecosystem &ndash; enabling consistent, reliable, and real-time access to features across development, training, and production environments. You&rsquo;ll collaborate closely with data scientists, ML engineers, and data platform teams to streamline feature engineering workflows and ensure seamless integration between offline and online data sources.
You&rsquo;ll be expected to work across multiple domains including data architecture, distributed systems, software engineering, and MLOps. You will help define and implement best practices for feature registration, drift, governance, lineage tracking, and versioning, all while contributing to the CI/CD automation that supports feature deployment across environments.
<h3 class="jobSectionHeader">What You&rsquo;ll Do
</h3>Key Responsibilities:
<ul><li>Feature Store Development: Implement and maintain scalable features serving offline (batch), online (real-time), and streaming ML use cases.
</li><li>Streaming &amp; Real-Time Data Processing: Design and manage streaming pipelines using technologies like Kafka, Kinesis, or Flink to enable low-latency feature generation and real-time inference.
</li><li>Feature Governance &amp; Lineage: Define and enforce governance standards for feature registration, metadata management, lineage tracking, and versioning to ensure data consistency and reusability.
</li><li>Collaboration with ML Teams: Partner with data scientists and ML engineers to streamline feature discovery, definition, and deployment workflows, ensuring reproducibility and efficient model experimentation.
</li><li>Data Pipeline Engineering: Build and optimize ingestion and transformation pipelines that handle large-scale data while maintaining accuracy, reliability, and freshness.
</li><li>CI/CD Automation: Implement CI/CD workflows and infrastructure-as-code to automate feature store provisioning and feature promotion across environments (Dev QA Prod).
</li><li>Monitoring &amp; Observability: Develop monitoring and alerting frameworks to track feature data quality, latency, and freshness across offline, online, and streaming systems.
</li></ul><h3 class="jobSectionHeader">What We&rsquo;re Looking For
</h3><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.
</li><li>5+ years of experience in data engineering roles.
</li><li>Strong proficiency in Python and familiarity with distributed data frameworks such as Airflow, Spark or Flink.
</li><li>Hands-on experience with feature store technologies (e.g., Feast, SageMaker Feature Store, Tecton, Databricks Feature Store, or custom implementations).
</li><li>Experience with cloud data warehouse (e.g., snowflake) and transformation framework (e.g. dbt) for data modeling, transformation and feature computation in batch environment.
</li><li>Expertise in streaming data platforms (e.g., Kafka, Kinesis, Flink) and real-time data processing architectures.
</li><li>Experience with cloud environments (AWS preferred) and infrastructure-as-code tools (Terraform, CloudFormation).
</li><li>Strong understanding of CI/CD automation, containerization (Docker, Kubernetes), and API-driven integration patterns.
</li><li>Knowledge of data governance, lineage tracking, and feature lifecycle management best practices.
</li><li>Experience with unstructured databases(vector or graph databases) and RAG pipelines
</li><li>Excellent communication skills, a collaborative mindset, and a strong sense of ownership.
</li></ul>Preferred Qualifications (Bonus Points):
<ul><li>Experience with Salesforce Ecosystem
</li><li>Experience with context engineering including structuring data, prompts, and logic for AI systems, managing memory and external knowledge, etc
</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.
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 $117,200 - $223,900 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 - MTS/SMTS

BCforward

<div>
 
 
 BCForward is currently seeking a highly motivated AWS Data Engineer for an On-site opportunity in Seattle, WA
 
 
 
 
 
 
 
 Role: AWS Data Engineer
 
 
 
 
 Duration: 6+ months
 
 
 
 
 Locations: Seattle, WA
 
 
 
 
 
 
 
 Anticipated Start Date:
 
 04/13/2026
 
 
 
 Job Type:
 
 Contract &ndash; Onsite
 
 
 
 
 
 We are looking for an AWS Data Engineer with strong experience in building and managing data solutions on AWS.
 
 
 
 
 
 
 Key Skills:
 
 AWS (EC2, S3, RDS, VPC), Python, Redshift (Must Have), AWS Glue, Athena, Lambda
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Build and maintain data pipelines and AWS infrastructure
 </li>
 <li>
 Work with Redshift for data warehousing and querying
 </li>
 <li>
 Use Glue, Athena, and Lambda for data processing and automation
 </li>
 <li>
 Support cloud deployments, monitoring, and troubleshooting
 </li>
 <li>
 Ensure security and compliance standards are followed
 </li>
 <li>
 Assist in migrating data and applications to AWS
 </li>
 </ul>
 
 
 
 
 
 Benefits:
 
 
 
 BCforward offers all eligible employees a comprehensive benefits package, including, but not limited to, major medical, HSA, dental, vision, employer-provided group life, voluntary life insurance, short-term disability, long-term disability, and 401k.
 
 
 
 
 
 
 About BCforward:
 
 
 
 Founded in 1998 on the idea that industry leaders needed a professional service and workforce management expert to
 
 
 fuel the development and execution of core business and technology strategies, BCforward is a Black-owned firm providing
 
 
 unique solutions supporting value capture and digital product delivery needs for organizations around the world.
 
 
 Headquartered in Indianapolis, IN, with an Offshore Development Center in Hyderabad, India, BCforward&rsquo;s 6,000
 
 
 Consultants support more than 225 clients globally.
 
 
 BCforward champions the power of human potential to help companies transform, accelerate, and scale. Guided by our
 
 
 With core values of People-Centric, Optimism, Excellence, Diversity, and Accountability, our professionals have helped our clients
 
 
 achieve their strategic goals for more than 25 years. Our strong culture and clear values have enabled BCforward to
 
 
 become a market leader and best in class place to work.
 
 
 BCforward is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against based on disability.
 
 
 To learn more about how BCforward collects and uses personal information as part of the recruiting process, view our Privacy Notice and CCPA Addendum. As part of the recruitment process, we may ask for you to disclose and provide us with various categories of personal information, including identifiers, professional information, commercial information, education information, and other related information. BCforward will only use this information to complete the recruitment process.
 
 
 This posting is not an offer of employment. All applicants applying for positions in the United States must be legally authorized to work in the United States. The submission of intentionally false or fraudulent information in response to this posting may render the applicant ineligible for the position. Any subsequent offer of employment will be considered employment at-will, regardless of the anticipated assignment duration.
 
</div>

AWS Data Engineer

Sparq

<div>
 At Sparq, we help companies solve the right problems&mdash;not just build more technology.
 
 
 We&rsquo;re a modern product engineering partner blending strategy, craftsmanship, and speed to help organizations modernize confidently in the age of AI. From data ecosystems to digital products and AI acceleration, we turn complexity into clarity and ideas into impact.
 
 
 If you&rsquo;re driven to build what&rsquo;s next, lead with empathy, and deliver excellence without ego, you&rsquo;ll feel right at home at Sparq.
 
 
 
 
 
 This opportunity will be on-site with our client
 
 
 
 
 
 
 
 C2C is not available
 
 
 
 
 
 
 Must be authorized to work in the U.S. without sponsorship
 
 
 
 
 
 Why You Will Enjoy Mondays Again
 
 
 
 <ul>
 <li>
 Opportunity to collaborate with a diverse group of colleagues in a fun, creative environment
 </li>
 <li>
 Progressive career journey and opportunity for advancement
 </li>
 <li>
 Continuous development through training, mentorship and certification programs
 </li>
 <li>
 Exposure to modern technologies across various industries in an agile environment
 </li>
 <li>
 Competitive salary + bonus opportunities
 </li>
 <li>
 Robust benefits package, matching 401(k) plan, and substantial PTO
 </li>
 <li>
 Tuition reimbursement
 
 
 </li>
 </ul>
 
 A Day In The Life
 
 
 
 <ul>
 <li>
 Develop and maintain scalable data pipelines to ensure the seamless flow of information across the organization.
 </li>
 <li>
 Troubleshoot and resolve issues within the existing ETL infrastructure and data warehousing components to minimize downtime.
 </li>
 <li>
 Design and deploy interactive dashboards in AWS QuickSight to provide stakeholders with real-time business insights.
 </li>
 <li>
 Proactively identify and automate manual data workflows to improve overall data quality and operational efficiency.
 </li>
 <li>
 Implement architectural optimizations to enhance the performance, reliability, and scalability of the current data stack.
 </li>
 <li>
 Document data models, pipeline designs, and operational procedures to ensure long-term knowledge sharing and maintenance.
 </li>
 <li>
 Collaborate on technical improvements using strong engineering discipline, including Git version control and peer code reviews.
 
 
 </li>
 </ul>
 
 What It Takes
 
 
 
 <ul>
 <li>
 3+ years of data engineering experience with a proven track record of building and optimizing scalable data pipelines.
 </li>
 <li>
 Advanced proficiency in SQL and Python for complex data modeling, transformation, and process automation.
 </li>
 <li>
 Hands-on experience with AWS Cloud Services, particularly QuickSight for visualization and ECS/EKS for containerized architectures.
 </li>
 <li>
 Strong software engineering discipline, including experience with testing frameworks and collaborative development in Git.
 </li>
 <li>
 Ability to manage and manipulate data within Smartsheet and integrate it into broader analytical workflows.
 </li>
 <li>
 Sharp problem-solving skills focused on identifying performance bottlenecks and streamlining data delivery.
 </li>
 <li>
 Clear technical communication skills for documenting complex system designs and operational logic.
 
 
 </li>
 </ul>
 
 Salary
 
 
 
 We consider a variety of factors when making compensation decisions. We share this to ensure transparency and set expectations for those
 
 
 considering opportunities with us.
 
 
 <ul>
 <li>
 The beginning salary range for this role is $90-110K
 
 
 </li>
 </ul>
 Regardless of your specific role, we seek individuals who are excited to explore, adopt, and evangelize AI tools and methodologies. If you have experience in AI or a proven track record of rapidly learning and mentoring others on emerging tech, you&rsquo;ll fit right in.
 
 
 
 
 Equal Employment Opportunity Policy: Sparq is proud to offer equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.
 
 
 
 
 
 
 We are committed to providing equal employment opportunities and believe in an inclusive workplace. If you require reasonable accommodations to participate in the job application or interview process, please let us know by contacting recruiting@teamsparq.com
 
 
 
 
 LI-ONSITE
 
 
 
 The Pay Range For This Role Is
 
 
 
 90,000 - 110,000 USD per year(Seattle, WA)
</div>

Data Analyst

Apple

As a Data Engineer on the Capacity Engineering team, you will help design, build, and operate the data foundation that drives capacity, cost, and power-related decisions across Apple&rsquo;s infrastructure footprint. 
 
In this role, you will: 
 
Architect, implement, and maintain large-scale batch and streaming pipelines that ingest, process, and model infrastructure telemetry, cost, metering, utilization, forecasting, and power metrics from multiple clouds and bare metal environments. 
 
Design and evolve robust data models (with a strong focus on dimensional modeling) and storage patterns that support analytics, internal billing, and efficiency use-cases. 
 
Treat data as a product: define quality checks, SLAs, and observability to ensure data is accurate, timely, and trusted by stakeholders across Apple. 
 
Integrate and enrich raw signals with metadata and attribution to power use cases such as internal billing/showback, usage understanding, efficiency and optimization, clawbacks, planning, and procurement. 
 
Collaborate closely with data scientists, software engineers, platform teams, finance partners, program managers, and leadership to translate requirements into scalable, reliable data solutions and services. 
 
Implement standard methodologies for data governance, lineage, metadata management, and security, in alignment with Apple&rsquo;s standards for data protection and privacy. 
 
Build end-to-end data solutions that include logging, anomaly detection, data validation, cleaning, and transformation, with strong emphasis on monitoring, debuggability, and continuous improvement. 
 
Contribute to the evolution of our data and platform stack, including tooling, frameworks, and standards for development, testing, deployment, and operations (CI/CD, infrastructure as code, etc.). 
 
Description 
 
Apple&rsquo;s Capacity data engineering team, within the Apple Services Engineering organization, is building the centralized data backbone that powers how Apple understands, plans, and optimizes its cloud and data center infrastructure. 
 
We engineer a unified, trusted data lake that consolidates cost, metering, utilization, forecasting, and power metrics produced by Apple platforms and systems (including bare metal) across both third-party and Apple internal clouds. Enriched with metadata and attribution, this becomes the single source of truth for internal billing, understanding usage and utilization, clawbacks, planning, procurement, and efficiency initiatives. 
 
We collaborate with platform engineering, finance, capacity engineering, and leadership teams to build large-scale data pipelines, enable descriptive and predictive analytics, and power dashboards and products that support critical business decisions. This is your opportunity to help design and operate highly visible, global-scale systems processing petabytes of data and supporting hundreds of users across Apple. 
 
Come join us to help deliver the next generation of infrastructure insights at Apple. 
 
Preferred Qualifications 
 
Advanced degree in a related field a plus. 
 
Experience with data visualization / BI tools, such as Superset or Tableau (other tools like QuickSight, QlikView, Cognos, or Business Objects are a plus) 
 
Experience with containerization and orchestration, such as Docker and Kubernetes/EKS is a plus 
 
Understanding of authentication and authorization (AuthN/AuthZ) patterns 
 
Knowledge of data governance principles, data security best practices, and data privacy regulations 
 
Minimum Qualifications 
 
Bachelors degree or equivalent experience in Computer Science, Information systems, Software Engineering, Data Science or related field. 
 
5+ years of experience in data engineering (or equivalent practical experience), including: 
 
Building and maintaining large-scale ETL/ELT data pipelines 
 
Distributed computing (e.g., Spark / PySpark) for data processing and automation 
 
Query performance optimization and tuning at scale 
 
Hands-on experience with: 
 
Apache Spark and Airflow (or similar workflow/orchestration tools) for efficient large-scale data pipelines 
 
Data modeling, especially dimensional modeling, and designing schemas optimized for analytics and reporting 
 
Big data platforms and/or data lake architectures 
 
Experience with CI/CD tooling such as Jenkins (or similar tools) 
 
Experience with cloud technologies, AWS/GCP (e.g., S3, EMR, Lambda, Glue, RDS/Redshift, Big-query, Kinesis or similar services) 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Data Engineer

<div>Do you want to play a part in the next revolution in Foundation Models? Contribute to model hillclimbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing? 
 
The vision for the AI/ML FM Data organization is to improve Foundation Models by leveraging data from a variety of sources: crawl, license, vendor and internal crowd-sourcing. As a Sr Software Engineering on the team, you will drive backend innovations, identify key opportunity areas where data can play a crucial role and experiment with various data augmentation strategies to improve model training efficiency and performance.. 
 
Description 
 
We are looking for people with a track record in building scalable pipelines and services. Join us, and impact hundreds of millions of customers across billions of their interactions with foundation model powered Apple Intelligence features, that are available on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages! 
 
As a Sr Backend Software engineer, you will be responsible for the following areas. 
 
<ul><li>Training data pipeline development. Convert raw data into format acceptable by training jobs on GCP and AWS. Leverage internal and open-sourced training modules.</li></ul> 
<ul><li>Large scale inferences: Leverage internal and open-sourced inference stack to generate inferences with fine-tuned LLMs on massive amounts of data, for pre-train and post-training</li></ul> 
<ul><li>Data processing and data filtering: Have the ability to efficiently process and filter very large amounts of data, often times messy.</li></ul> 
<ul><li>Scalable web services backend and APIs to support data access and data inspection tools</li></ul> 

Preferred Qualifications 
 
Familiarity with streaming-processing (Kafka). Familiarity with a variety of build tools (Jenkins, Maven, Docker, Gradle). 
 
Experience providing architecture and design guidance. 
 
A good communicator with clear and concise, active listening and empathy skills. 
 
Are self-motivated and curious. Strive to continually learn on the job. 
 
Have demonstrated creative and critical thinking with an innate drive to improve how things work. Have a high tolerance for ambiguity. 
 
Minimum Qualifications 
 
BS in Computer Science or Equivalent. 
 
10+ years of programming experience in Python. Extensive experiences in concurrency and parallelism, functional programming, decorators. Familiarity in other programming languages (Java/GoLang/Rust/Swift). 
 
Proficient in REST API, Redis, VectorDB or other large scale data storage systems. 
 
Solid foundational programming skills (algorithms, data structures, OOP, etc). 
 
Experience designing, writing, reviewing, testing and delivering software for applications and systems at scale. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</div>

AIML - Sr Backend Engineer, Data and ML Innovation

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
About the team 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

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