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Bloomberg

<div><div><div><div><div><div>Senior Data Management Professional - Company Financials, Analytics Engineer
</div></div></div></div></div><div><div><div><div><div>Location
</div><div>New York
</div></div><div><div>Business Area
</div><div>Data
</div></div><div><div>Ref #
</div><div>10049339
</div></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description &amp; Requirements
</b></h2></div></div><div><div><div><div><div>Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock &ndash; from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology&mdash;quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.<br>
</div><div></div><br>
<div>Our Team
</div><div>The Company Financials (CoFi) Data team provides clients with fast, accurate, and trusted financial data that powers analysis across markets and industries. Our datasets support reporting, modeling, and insight generation for internal stakeholders and external clients.<br>
</div><div></div><br>
<div>We combine financial domain expertise, data modeling, analytics engineering, and technical rigor to create high-quality, performant analytical datasets that support a wide range of reporting and decision-making needs.<br>
</div><div></div><br>
<div>What's the role?
</div><div>As a Senior Data Management Professional within the Business Intelligence team, you will play a key role in shaping and evolving the analytical data foundations that power our reporting platform.<br>
</div><div></div><br>
<div>This is a hands-on, data-focused role centered on building, modeling, and optimizing analytical datasets. You will own and evolve Foundational Reporting Datasets (FRDs), ensuring they are accurate, performant, reusable, and aligned with domain realities. You will work closely with domain experts, Product, and Engineering partners to translate complex, real-world financial data into stable analytical schemas that support scalable reporting and reuse.<br>
</div><div></div><br>
<div>Your work will directly influence how data is trusted, modeled, and reused across teams, balancing immediate analytical needs with long-term scalability and governance.<br>
</div><div></div><br>
<div>We'll trust you to:
</div><ul><li>Build, maintain, and evolve Foundational Reporting Datasets (FRDs) that serve as the analytical backbone for reporting and analysis
</li></ul><ul><li>Write and optimize SQL queries to clean, shape, and model noisy, real-world data into performant, reusable datasets
</li></ul><ul><li>Make pragmatic tradeoffs around correctness, scope, performance, and documentation, reasoning about data semantics and grain
</li></ul><ul><li>Continuously improve data quality, clarity, and query efficiency
</li></ul><ul><li>Work closely with domain experts and stakeholders to understand how the data is produced, interpreted, and used
</li></ul><ul><li>Actively build domain intuition over time &mdash; learning why the data behaves the way it does, not just how it&rsquo;s structured
</li></ul><ul><li>Represent the data accurately and confidently in cross-functional discussions
</li></ul><ul><li>Identify analytical work that is worth formalizing into reusable data products
</li></ul><ul><li>Help define clear boundaries between foundational datasets and decision-specific, reusable data products
</li></ul><ul><li>Collaborate with a Product Manager who owns roadmap and prioritization, providing deep input into feasibility and tradeoffs
</li></ul><ul><li>Partner with engineers on performance, tooling, and modeling decisions, while remaining focused on the data layer itself<br>
</li></ul><div></div><br>
<div>You'll need to have:
</div><ul><li>4+ years of experience as a BI analyst, analytics engineer, or similar data-focused role</li></ul>
<ul><li>Deep hands-on experience with, SQL-based data modeling, PySpark and Pandas/Polars, analytical dataset design, performance and efficiency considerations as well as storage/layout optimization for analytical tables
</li></ul><ul><li>Experience designing for schema evolution and the ability to source validation and data profiling
</li></ul><ul><li>Proven ability to turn messy, ambiguous data into trusted analytical assets
</li></ul><ul><li>Comfort working under ambiguity and improving things incrementally
</li></ul><ul><li>Strong collaboration skills and interest in learning a data domain deeply
</li></ul><ul><li>Ability to translate semi-structured producer data into stable analytical schemas (OLTP to OLAP)<br>
</li></ul><div></div><br>
<div>We'd love to see:
</div><ul><li>Experience working with complex or regulated datasets
</li></ul><ul><li>Experience using Bloomberg Terminal and Company Financials products
</li></ul><ul><li>Exposure to data product or platform-style thinking
</li></ul><ul><li>Experience partnering closely with domain experts or SMEs
</li></ul><ul><li>Experience driving adoption of new systems
</li></ul><ul><li>Interest in data governance, ownership, and reuse patterns
</li></ul><ul><li>Familiarity with modern table formats and distributed query engines at scale (e.g., Iceberg/Delta; Trino/Spark or equivalents)
</li></ul><ul><li>Exposure to high-concurrency BI serving patterns (OBT)</li></ul>
</div></div><div></div><div><div><div>Salary Range = 110000 - 190000 USD Annually + Benefits + Bonus</div><div><br>
<div><br>
</div><div>The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.<div><br>
<br>
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.<br>
</div></div></div></div></div><div><div>Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.</div></div></div></div></div></div>

Senior Data Management Professional - Company Financials, Analytics Engineer

Genpact

<p></p><div><div><div><div><div><b><i>Ready to build the future with AI?</i></b></div></div><div><div><b><i>
At Genpact, we don&rsquo;t just keep up with technology&mdash;we set the pace. AI and digital innovation are redefining industries, and we&rsquo;re leading the charge. Genpact&rsquo;s </i></b><b><i>AI Gigafactory</i></b><b><i>, our industry-first accelerator, is an example of how we&rsquo;re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to </i></b><b><i>agentic AI</i></b><b><i>, our breakthrough solutions tackle companies&rsquo; most complex challenges.</i></b></div></div><div><div><b><i>
If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquo;s possible, this is your moment.</i></b></div></div><div><div><b><i>
Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions &ndash; we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at </i></b><b><i>genpact.com </i></b><b><i>and on </i></b><b><i>LinkedIn</i></b><b><i>, </i></b><b><i>X</i></b><b><i>, </i></b><b><i>YouTube</i></b><b><i>, and </i></b><b><i>Facebook</i></b><b><i>.</i></b></div></div><div></div><div><div><b><br>
Inviting applications for the role of Senior Engineer - Big Data and Business Intelligence</b></div></div><div></div><div><div><b><br>
Skills &ndash; Headstrong Services LLC seeks Senior Engineer - Big Data and Business Intelligence (multiple positions) in New York NY to analyze petabytes of structured and unstructured data hosted on cloud, flat files, and a variety of databases (traditional, NoSQL, columnar and in-memory) and create technology road map for data integration. Prepare technical </b><b>design</b><b>outlining detailed instructions and logical steps required for coding. Develop, optimize, automate, and maintain software programs, algorithms, and prototypes to handle everyday big data problems. Collect, parse, transform, store, and visualize large sets of data to help end customers unlock the power of data insights and data driven decision-making. Research and recommend software and tools that are pivotal for building impactful data products. Supervise, coach, and mentor junior data engineers. Utilize experience with: Informatica Suite (PowerCenter, Intelligent Cloud Service, and Big Data Management); Amazon Cloud Services (S3, EC2, and EMR); Big Data tools (MapReduce, Spark, or similar); Relational databases (Oracle Exadata); Programming Languages (SQL, PL/SQL); NoSQL Databases (MongoDB or similar); Data </b><b>Visulazation</b><b>tools (Business Objects, Tableau or similar).</b></div></div><div></div><div><div><b><br>
Education &ndash; Position requires a </b><b>Master&rsquo;s</b><b>degree in an Engineering (all), Computer Science, Sciences, Mathematics, or a related field and 2 years of experience in the job offered, a related software engineering, programmer, or systems analyst position, or related occupation. As an alternative, a </b><b>Bachelor&rsquo;s</b><b>degree in an Engineering (all), Computer Science, Sciences, Mathematics, or a related field and 5 years of progressively responsible post-Bachelor's experience in the job offered, a related software engineering, programmer, or systems analyst position, or related occupation is acceptable. Foreign equivalent degrees are acceptable. Position also requires 2 years of experience with the following: Informatica suite (PowerCenter, Intelligent Cloud Services, Big Data Management); Amazon Cloud Services (S3, EC2, EMR); Big Data tools (MapReduce, Spark or similar); Relational Databases (Oracle Exadata); Programming Languages (SQL, PL/SQL); NoSQL Databases (MongoDB or similar); and Data Visualization Tools (Business Objects, Tableau or similar). Position headquartered in New York, NY with placement at project sites nationally within the United States with no additional travel required. $189,592 to $199,071 per year.</b></div></div><div></div><div><div><b><br>
Please send resume and cover letter to:</b></div></div><div></div><div><div><b><br>
Talent.Recruitment@genpact.com</b></div></div><div></div><div><div><b><br>
Indicate job code &ldquo;HSSEBDBINY0326&rdquo; when applying.</b></div></div><div></div><div><div><b><i><br>
Why join Genpact?</i></b></div></div><div><ul><div><div><b><i>
Lead AI-first transformation &ndash; Build and scale AI solutions that redefine industries</i></b></div></div></ul></div></div><div><div><ul><div><div><b><i>
Make an impact &ndash; Drive change for global enterprises and solve business challenges that matter</i></b></div></div></ul></div><div><ul><div><div><b><i>
Accelerate your career&mdash;Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills</i></b></div></div></ul></div><div><ul><div><div><b><i>
Grow with the best &ndash; Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace</i></b></div></div></ul></div><div><ul><div><div><b><i>
Committed to ethical AI &ndash; Work in an environment where governance, transparency, and security are at the core of everything we build</i></b></div></div></ul></div><div><ul><div><div><b><i>
Thrive in a values-driven culture &ndash; Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress</i></b></div></div></ul></div><div><div><b><i>
Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up.</i></b></div></div><div><div><b><i>
Let&rsquo;s build tomorrow together.</i></b></div></div><div></div><div><div><b><i><br>
The approximate annual base compensation range for this position is $189,592 to $199,071. The actual offer, reflecting the total compensation package plus benefits, will be determined by </i></b><b><i>a number of</i></b><b><i>factors which include but are not limited to the applicant&rsquo;s experience, knowledge, skills, and abilities; geographic location; and internal equity</i></b></div></div><div></div><div><div><b><i><br>
&ldquo;Los Angeles, California based candidates are not eligible for this role.</i></b></div></div><div></div><div><div><b><i><br>
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, </i></b><b><i>color</i></b><b><i>, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.</i></b><br>
<b><i>Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.</i></b></div></div></div></div><p></p><p><br>
JobPrincipal Consultant</p><p>
Primary LocationUSA-New York</p><p>
ScheduleFull-time</p><p>
Education LevelBachelor's / Graduation / Equivalent</p><p>
Job PostingMar 12, 2026, 7:50:08 AM</p><p>
Unposting DateApr 11, 2026, 1:29:00 PM</p><p>
Master Skills ListConsulting</p><p>
Job CategoryFull Time</p></div>

Senior Engineer - Big Data and Business Intelligence

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.<br>
</li>
<li>5 years of experience programming in Python or C++.</li>
<li>3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.<br>
</li>
<li>3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).</li>
<li>1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree or PhD in Computer Science or related technical field.<br>
</li>
<li>5 years of experience with data structures/algorithms.</li>
<li>1 year of experience in a technical leadership role.<br>
</li>
<li>Experience developing accessible technologies.<br>
</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
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.</p>
<p>
AI will change the future of work in profound ways, and our products&mdash; Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.</p><p>
The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.</p><p>
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Write and test product or system development code.<br>
</li>
<li>Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).<br>
</li>
<li>Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.<br>
</li>
<li>Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.<br>
</li>
<li>Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.<br>
</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>

Senior Software Engineer, AI/ML GenAI, Google Workspace

Major League Soccer

<div>Overview:
<div>
Major League Soccer has built Fan Genome, a 360&deg; fan intelligence platform unifying demographic, behavioral, transactional, and engagement data across the league. MLS operates a modern cloud-native Lakehouse architecture built on medallion design, decoupled storage and compute, and distributed processing at scale.</div><div><br>
We are seeking a Director of Analytics Engineering &amp; BI Platform to lead the analytics engineering function and fully enable the BI organization on top of this existing foundation. This role focuses on curating scalable data products, standardizing enterprise metrics, strengthening semantic governance, and ensuring BI and AI use cases are supported by trusted, high-performance datasets.</div>
Responsibilities:
<div><b>
Lakehouse Enablement and Analytics Integration</b></div><ul><li>
Leverage MLS&rsquo;s existing Lakehouse architecture across bronze, silver, and gold layers to deliver scalable analytics and BI-ready data products.</li><li>
Define modeling, transformation, and serving standards that align analytics engineering workflows with the underlying platform.</li><li>
Partner with data engineering to ensure ingestion pipelines and core datasets support downstream BI and semantic requirements.</li><li>
Establish best practices for incremental processing, schema evolution, and open table usage within analytics use cases.</li><li>
Structure analytics workloads to take full advantage of decoupled storage and distributed compute capabilities.</li></ul><div><b>
Analytics Engineering &amp; Domain Data Products</b></div><ul><li>
Lead development and refinement of curated gold-layer datasets aligned to fan, commerce, content, and engagement domains.</li><li>
Implement scalable transformation frameworks leveraging distributed compute engines such as Spark or equivalent.</li><li>
Design domain-oriented data products built on large, incrementally processed tables rather than fragmented reporting schemas.</li><li>
Standardize transformation logic, automated testing, version control, CI/CD, and lineage tracking.</li><li>
Ensure data products are reusable, well-documented, and trusted across the organization.</li></ul><div><b>
BI Curation &amp; Enterprise Enablement</b></div><ul><li>
Curate and optimize analytics datasets specifically for Power BI and other enterprise BI tools.</li><li>
Design scalable BI-ready datasets that balance usability, governance, and performance.</li><li>
Optimize semantic models for query performance, refresh efficiency, and executive reporting requirements.</li><li>
Establish standards for dataset certification, lifecycle management, and metric consistency.</li><li>
Define best practices for incremental refresh, aggregation strategies, and performance tuning within Power BI.</li><li>
Provide structured partnership and ongoing support to ensure the BI team is fully enabled with stable, performant, and governed datasets.</li></ul><div><b>
Semantic Governance &amp; Knowledge Graph</b></div><ul><li>
Operate and evolve a centralized semantic layer that standardizes KPI definitions, hierarchies, and metric logic.</li><li>
Encode business rules programmatically to eliminate duplication across dashboards and downstream systems.</li><li>
Maintain a pragmatic semantic knowledge graph capability to model key entities and relationships across fan, commerce, and engagement domains.</li><li>
Ensure semantic assets are machine-readable and consistent across BI, APIs, and AI use cases.</li><li>
Implement metric certification, versioning, and change management processes.</li></ul><div><b>
Data Quality, Observability &amp; Contracts</b></div><ul><li>
Implement and mature a comprehensive data quality framework across medallion layers.</li><li>
Define SLAs for critical datasets and enterprise KPIs.</li><li>
Establish automated validation, reconciliation testing, anomaly detection, and freshness monitoring.</li><li>
Embed quality controls and semantic validation into analytics workflows.</li><li>
Formalize data and semantic contracts between upstream producers and BI consumers.</li></ul><div><b>
AI-Ready Data &amp; Metadata Foundations</b></div><ul><li>
Translate business logic and KPI definitions into structured, machine-readable representations.</li><li>
Maintain metadata-driven documentation capturing metric logic, lineage, and transformation dependencies.</li><li>
Ensure BI datasets and semantic assets are prepared for AI and advanced analytics use cases.</li><li>
Support integration with feature stores and emerging AI workflows where appropriate.</li></ul><div><b>
BI &amp; Asset Migration</b></div><ul><li>
Lead structured migration of legacy reporting assets and fragmented BI datasets into the unified Lakehouse and semantic architecture.</li><li>
Define migration playbooks including inventory, reconciliation, validation, parallel runs, and deprecation planning.</li><li>
Ensure metric parity and stakeholder confidence during transitions.</li></ul><div><b>
Leadership, Team Management &amp; Stakeholder Partnership</b></div><ul><li>
Lead, manage, and develop a high-performing analytics engineering team, including hiring, coaching, and performance management.</li><li>
Establish clear goals, operating rhythms, and accountability frameworks.</li><li>
Create career paths aligned to modern analytics engineering practices.</li><li>
Serve as a data champion across the organization, promoting enterprise data standards and metric consistency.</li><li>
Establish clear operating models across data engineering, analytics engineering, BI, and AI teams.</li><li>
Partner with executive stakeholders to translate business KPIs into governed semantic models and scalable data products.</li><li>
Foster a culture centered on engineering rigor, data quality, collaboration, and stakeholder alignment.</li></ul>
Qualifications:
<div><b>
E</b><b>ducation and Experience</b></div><ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, or related field required. Advanced degree preferred.</li><li>
10+ years of experience working with modern cloud-native data platforms and enterprise BI ecosystems.</li><li>
8+ years leading engineering or analytics teams in distributed data environments.</li></ul><div><b>
Required skills</b></div><div><br>
</div><div><b>Modern Lakehouse &amp; Distributed Systems</b></div><ul><li>
Proven experience working within large-scale Lakehouse architectures with medallion modeling.</li><li>
Strong understanding of decoupled storage and compute architectures.</li><li>
Experience with open table formats such as Apache Iceberg or Apache Hudi.</li><li>
Expertise in distributed processing engines such as Apache Spark.</li><li>
Experience designing analytics workflows over large tables in object storage environments.</li></ul><div><b>
BI Curation &amp; Power BI Expertise</b></div><ul><li>
Strong experience designing, optimizing, and governing Power BI datasets at scale.</li><li>
Deep understanding of semantic modeling within Power BI, including measures, calculation groups, incremental refresh, and performance tuning.</li><li>
Experience building certified enterprise datasets supporting executive reporting and self-service analytics.</li><li>
Ability to align Lakehouse data products with BI consumption-layer requirements.</li></ul><div><b>
Analytics Engineering &amp; Semantic Modeling</b></div><ul><li>
Experience designing domain-oriented data products in Lakehouse environments using medallion layering and distributed transformations.</li><li>
Demonstrated experience building governed semantic layers and enterprise metrics frameworks.</li><li>
Ability to encode business rules programmatically and maintain machine-readable metric logic.</li><li>
Working knowledge of semantic knowledge graph concepts and entity relationship modeling.</li></ul><div><b>
Data Quality &amp; Observability</b></div><ul><li>
Experience implementing automated data validation frameworks in distributed architectures.</li><li>
Strong understanding of reconciliation testing, SLA enforcement, and lineage tracking at scale.</li></ul><div><b>
AI-Ready Data Systems</b></div><ul><li>
Familiarity with feature stores, embeddings, and vector indexing concepts.</li><li>
Experience maintaining metadata-driven systems that support machine-readable business semantics and AI consumption of analytics assets.</li></ul><div></div><div><b><br>
Total Rewards</b></div><div>
Major League Soccer offers a competitive starting base salary of $200,000 - $230,000.00, based on individual qualifications, market financials, and operational business needs. We are committed to providing a Total Rewards package that attracts, supports, engages, and retains talent. Our benefits package includes comprehensive medical, dental, and vision coverage, a $500 wellness reimbursement, and generous Holiday and PTO schedule to promote work-life balance. We also prioritize career and professional development, offering on-the-job training, feedback, and ongoing educational opportunities.</div><div></div><div><br>
We believe in the power of in-person collaboration to fuel creativity, strengthen connections, and cultivate a vibrant workplace. As a result, employees are required to work from an MLS office at least four days a week. We understand the value of balance, so employees also have the flexibility of working remotely on Fridays, along with the option to take up to two additional remote flex days each month.</div><div></div><div><br>
At Major League Soccer, we are proud to be an equal opportunity employer. We value diversity and inclusion and believe that a diverse workforce enhances our ability to compete in the marketplace. We are committed to providing equal employment opportunities to all individuals regardless of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.</div><div></div><div><br>
We are dedicated to ensuring that individuals with disabilities are provided reasonable accommodation throughout the job application or interview process, essential job functions, and other benefits and privileges of employment. If you require accommodation, please contact us to request it.</div><div></div><div><br>
Join our team and be part of the Major League Soccer family, where we elevate the game and inspire greatness!</div></div>

Senior Director, Analytics Engineering and BI Platform

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon&rsquo;s custom machine learning accelerators, Inferentia and Trainium.<br>
<br>
The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance.<br>
<br>
The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.<br>
<br>
As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology<br>
<br>
You will architect and implement business critical features, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers.<br>
<br>
This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond. The Inference Enablement and Acceleration team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing inference performance for both latency and throughput on such large models across the stack from system level optimizations through to Pytorch or JAX is a must have.<br>
<br>
You can learn more about Neuron<br>
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html<br>
https://aws.amazon.com/machine-learning/neuron/<br>
https://github.com/aws/aws-neuron-sdk<br>
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success<br>
<br>
Key job responsibilities<br>
This role will help lead the efforts in building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python, System level programming and ML knowledge are both critical to this role. Our engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration. In this role, you will:<br>
<br>
<ul><li>Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.</li><li>Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, hardware-specific optimizations, testing and production deployment.</li><li>Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.</li><li>Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models</li><li>Analyze and optimize system-level performance across multiple generations of Neuron hardware</li><li>Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks</li><li>Implement optimizations such as fusion, sharding, tiling, and scheduling</li><li>Conduct comprehensive testing, including unit and end-to-end model testing with continuous deployment and releases through pipelines.</li><li>Work directly with customers to enable and optimize their ML models on AWS accelerators</li><li>Collaborate across teams to develop innovative optimization techniques</li></ul><br>
A day in the life<br>
You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. As you design and code solutions to help our team drive efficiencies in software architecture, you&rsquo;ll create metrics, implement automation and other improvements, and resolve the root cause of software defects.<br>
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You will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you&rsquo;re always working on the most important initiative.<br>
<br>
About the team<br>
The Inference Enablement and Acceleration team fosters a builder&rsquo;s culture where experimentation is encouraged, and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we&rsquo;re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of non-internship professional software development experience</li><li>Bachelor's degree in computer science or equivalent</li><li>5+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on optimizations for improving the model execution.</li><li>Software development experience in C++, Python (experience in at least one language is required).</li><li>Strong understanding of system performance, memory management, and parallel computing principles.</li><li>Proficiency in debugging, profiling, and implementing best software engineering practices in large-scale systems.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Familiarity with PyTorch, JIT compilation, and AOT tracing.</li><li>Familiarity with CUDA kernels or equivalent ML or low-level kernels.</li><li>Candidates with performant kernel development such as CUTLASS, FlashInfer etc., would be well suited.</li><li>Familiar with syntax and tile-level semantics similar to Triton.</li><li>Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments.</li><li>Deep understanding of computer architecture, operation systems level software and working knowledge of parallel computing.</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.<p><br>
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.</p><br>
USA, NY, New York - 184,900.00 - 250,200.00 USD annually<br>
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually</div><p></p>

Senior Software Development Engineer - AI/ML, AWS Neuron, Multimodal Inference

Apple

<p>At Apple, we focus deeply on our customers&rsquo; experience. Apple Ads brings this same approach to advertising, helping people find exactly what they&rsquo;re looking for and helping advertisers grow their businesses!<br>
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Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!<br>
<br>
<b>Description</b><br>
<br>
We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple&rsquo;s App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment.<br>
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You&rsquo;ll work at the intersection of applied ML, deep learning, and retrieval systems-developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple&rsquo;s ad prediction systems.<br>
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&quot;,&quot;responsibilities&quot;:&quot;Design and implement ML models to improve predictions of user interaction, click-through rate (CTR), and conversion rate (CVR)<br>
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Develop and optimize retrieval algorithms, leveraging techniques from classical IR and modern deep learning<br>
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Contribute to core modeling areas such as deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals<br>
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Work with large-scale, distributed datasets to identify new signals and improve model accuracy and robustness<br>
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Collaborate with cross-functional teams across engineering, infrastructure, and product to scale models to production<br>
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Participate in designing and running large-scale experiments to validate new model architectures and learning strategies<br>
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<b>Preferred Qualifications</b><br>
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MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.<br>
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Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus<br>
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<b>Minimum Qualifications</b><br>
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6+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval<br>
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Deep experience with neural network architectures (e.g., Transformers, DNNs, RNNs) and training pipelines using TensorFlow, PyTorch<br>
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Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization<br>
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Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale<br>
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Proficient in Python and familiar with SQL, Scala, or Java for production environments<br>
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Ability to translate abstract ideas into concrete, high-impact solutions<br>
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Bachelor's, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.<br>
<br>
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 .<br>
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<b>Pay &amp; Benefits</b><br>
<br>
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 $212,000 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.<br>
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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.<br>
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Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Senior Machine Learning Engineer - Ads Predictions

James Search Group

<div>
 <p>
  <strong>
   AI/ML Engineer
  </strong>
 </p>
 <p>
  <strong>
   Location:
  </strong>
  New York, NY
 </p>
 <p>
  <strong>
   Compensation:
  </strong>
  $135,000 &ndash; $175,000 base + bonus + full benefits, (401(k), and more)
 </p>
 <p>
  <strong>
   Industry:
  </strong>
  Global P&amp;C Insurance
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the role and the company.
  </strong>
 </p>
 <p>
  James Search Group is working closely with a top-tier global property &amp; casualty insurance carrier to identify an
  <strong>
   AI/ML Engineer
  </strong>
  to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.
 </p>
 <p>
  <br/>
 </p>
 <p>
  As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities:
  </strong>
 </p>
 <ul>
  <li>
   Support the development and deployment of AI/ML models&mdash;including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
  </li>
  <li>
   Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
  </li>
  <li>
   Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
  </li>
  <li>
   Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications:
  </strong>
 </p>
 <ul>
  <li>
   Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
  </li>
  <li>
   Minimum of 2 years&rsquo; experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
  </li>
  <li>
   Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
  </li>
  <li>
   Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
  </li>
  <li>
   Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Qualifications:
  </strong>
 </p>
 <ul>
  <li>
   Internship or project experience in machine learning, AI engineering, or related roles&mdash;especially in insurance or financial services.
  </li>
  <li>
   Familiarity with actuarial concepts or insurance-specific data models.
  </li>
  <li>
   Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
  </li>
  <li>
   Comfortable in a collaborative, fast-paced, and agile working environment.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Apply today
  </strong>
  to help reshape the future of insurance through data and AI innovation.
 </p>
</div>


Machine Learning Engineer

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