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aiml sr backend engineer data and ml innovation

Apple

<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

The Apple Ray team is seeking a Senior / Staff Software Engineer with strong distributed systems expertise and a solid background in machine learning. In this hybrid role, you will design and build core components of Apple&rsquo;s unified data+ML platform powered by open-source Ray, while also partnering with ML teams to ensure the platform meets the needs of large-scale training and inference workloads. 
 
You will contribute to the distributed runtime, orchestration layer, and system APIs that power Apple&rsquo;s intelligent features across products and services. This role is ideal for a software engineer who enjoys low-level systems work but is also fluent in ML workflows and models at scale. 
 
Description 
 
Apple Ray integrates deeply with Apple&rsquo;s data and ML ecosystem to provide a unified platform for building, orchestrating, and scaling complex ML and data pipelines. As a Software Engineer with ML background, you will design distributed systems that support large-scale model training, tuning, and inference across heterogeneous compute environments-from bare-metal GPU clusters to cloud-native infrastructure. 
 
You will build features that enhance developer productivity for ML engineers, improve resource efficiency, and advance the performance and reliability of Apple&rsquo;s ML workloads. You&rsquo;ll collaborate closely with ML practitioners to translate model and pipeline needs into robust platform capabilities, while also improving the underlying distributed runtime and control plane. 
 
This role requires strong engineering fundamentals, hands-on experience with ML systems, and a passion for building scalable infrastructure.&quot;,&quot;responsibilities&quot;:&quot;Build scalable distributed systems and platform components using Ray that power Apple&rsquo;s data+ML workflows. 
 
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines. 
 
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale. 
 
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features. 
 
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs. 
 
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability. 
 
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads. 
 
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools. 
 
Preferred Qualifications 
 
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO). 
 
Background in optimizing GPU workloads or performance benchmarking. 
 
Experience with model orchestration systems or ML platforms. 
 
Contributions to open-source ML or distributed systems projects. 
 
Familiarity with large-scale data systems such as Spark, Flink, or similar. 
 
Minimum Qualifications 
 
6+ years building distributed systems, high-scale backend services, or compute runtimes. 
 
Solid background in ML workflows, model training, model serving, or data pipeline development. 
 
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java). 
 
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training. 
 
Understanding of parallelism strategies, model scaling, or distributed training concepts. 
 
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems. 
 
Strong debugging skills across distributed and ML-centric runtime environments. 
 
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams. 
 
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience. 
 
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 $171,600 and $302,200, 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 / Staff ML Engineer, Apple Ray, Apple Data Platform

Uber

<div>
 
 About The Role
 
 
 
 Earner Incentives is one of the fastest-growing products at Uber. As an Engineer on the Earner Incentives team you will work on the latest backend technologies developing highly scalable, Customer facing services and features, platforms and control panel tooling used by our operations on a daily basis.
 
 
 Incentives Platform is used for generating efficient incentives for drivers, measuring progress of drivers towards achieving those incentives and then paying once incentive goals are achieved. It plays a critical role in ensuring adequate supply to meet the market demands across time and space. The combination of technical challenges and cross functional work will allow you to grow as a software engineer in any dimension.
 
 
 Join us to work on some of the most exciting challenges on this journey.
 
 
 
 What The Candidate Will Need / Bonus Points
 
 
 
 ---- What the Candidate Will Do ----
 
 
 <ul>
 <li>
 As a backend engineer, you will architect, design and build software solutions to help with all aspects of capacity planning/management/engineering to scale Uber's infrastructure across a variety of sophisticated workflows and business processes.
 </li>
 <li>
 Design end-to-end features and systems to build high quality consumer-facing products.
 </li>
 <li>
 Write code, test, and maintain production services for high availability, reliability, and performance.
 </li>
 <li>
 Work with ML engineers and scientists to develop ML models to improve product performance.
 </li>
 <li>
 Work with Product Managers to understand product requirements and lead product rollout plans.
 </li>
 <li>
 Mentor junior team members.
 </li>
 <li>
 You will collaborate with other teammates to maintain the health of our systems and codebase, refactor and make improvements, and keep our systems robust and resilient.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 2+ years experience working on the full software life cycle including gathering requirements, project planning, solution design, coding/implementation, testing, rollout/deployment and best practices as an individual contributor.
 </li>
 <li>
 Experience coding using general purpose programming language (eg. C/C++, Java, Python, Go, C#)
 </li>
 <li>
 Fast and passionate learner. Strong collaboration, documentation and communication skills.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience building consumer-facing products.
 </li>
 <li>
 Experience designing and implementing large-scale service with excellent quality.
 </li>
 <li>
 Experience working with Machine Learning engineers and scientists on ML model productionization.
 </li>
 <li>
 Experience collaborating with other engineers and non-tech stakeholders, both to meet short-term goals and to create long-term partnerships.
 
 
 </li>
 </ul>
 For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits., For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
</div>

Software Engineer II - Earner Incentive

<div>
 
 Summary
 
 
 
 Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide!
 
 
 As part of Apple's AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges.
 
 
 
 Description
 
 
 
 As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem.
 
 
 You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models.
 
 
 Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
 
 
 Your work may span a variety of directions, including but not limited to:
 
 
 Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data.
 
 
 Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets.
 
 
 Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models.
 
 
 Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data.
 
 
 Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments.
 
 
 Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
 </li>
 <li>
 Deep understanding in multi-modal foundation models.
 </li>
 <li>
 Staying on top of emerging trends in generative AI and multi-modal LLM.
 </li>
 <li>
 Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
 </li>
 <li>
 Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc)
 </li>
 <li>
 Strong problem-solving and communication skills.
 </li>
 <li>
 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas
 
 
 </li>
 </ul>
 
 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 $147,400 and $272,100, 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&rsquo;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&rsquo;s Employee Stock Purchase Plan. You&rsquo;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 &mdash; 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.
 
 
 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.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

AIML - Machine Learning Engineer, Data and ML Innovation

GEICO

<div>At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers&rsquo; expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here. That&rsquo;s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers
GEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization&mdash;designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes. 
You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologies
About the role<ul><li>
Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.</li><li>
Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.</li><li>
GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.</li></ul>
What you&rsquo;ll do<ul><li>
Own ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.</li><li>
Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.</li><li>
Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).</li><li>
Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact.</li><li>
Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.</li><li>
Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems.</li><li>
Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.</li><li>
Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence.</li><li>
Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.</li><li>
Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices.</li><li>
Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards.</li><li>
Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.</li></ul>
Minimum qualifications<ul><li>
Bachelor&rsquo;s degree or above in Computer Science, Engineering, Statistics, or related field.</li><li>
10+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#).</li><li>
10+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components:<ul><li>
Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval)</li><li>
Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg</li><li>
Streaming: Kafka; plus Flink/Spark Streaming experience</li><li>
Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra)</li><li>
Distributed compute: Spark, Ray</li><li>
Workflow orchestration: Airflow, Temporal</li></ul></li><li>
6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.</li><li>
6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.</li></ul>
Preferred qualifications (GenAI as a plus)<ul><li>
Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling.</li><li>
Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks.</li><li>
Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.</li><li>
Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices.</li><li>
Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.</li><li>
Experience with high-throughput, low-latency inference and real-time feature pipelines.</li></ul>
#LI-JK1 
Annual Salary
$150,000.00 - $300,000.00
The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate&rsquo;s work experience, education and training, the work location as well as market and business considerations. 

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position. 
The GEICO Pledge:
Great Company: At GEICO, we help our customers through life&rsquo;s twists and turns. Our mission is to protect people when they need it most and we&rsquo;re constantly evolving to stay ahead of their needs.
We&rsquo;re an iconic brand that thrives on innovation, exceeding our customers&rsquo; expectations and enabling our collective success. From day one, you&rsquo;ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people&rsquo;s lives.
Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career &ndash; and your potential &ndash; in mind. You&rsquo;ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.
Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.<ul><li>
Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family&rsquo;s overall well-being.</li><li>
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.</li><li>
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.</li><li>
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.</li></ul>
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.</div>

Senior Staff Machine Learning Engineer

Cerebro

<div>
 
 Are you passionate about advancing the frontier of AI? Do you thrive at the intersection of cutting-edge research and real-world impact? A fast-growing AI startup is looking for exceptional AI researchers and engineers with expertise in
 
 multimodal models
 
 to join their world-class team in
 
 Seattle, WA
 
 .
 
 
 
 About Us
 
 
 
 We are a well-funded startup backed by top-tier investors, with a mission to bring real-time AI avatars to life. Our team includes experts with advanced degrees from leading institutions and extensive experience at top tech companies. With significant funding and a clear vision, we are scaling rapidly and looking for top talent to help operationalize cutting-edge research into transformative products.
 
 
 
 What You&rsquo;ll Do
 
 
 
 As an
 
 AI Research Engineer
 
 , you&rsquo;ll play a pivotal role in bridging the gap between research and production. Your responsibilities will include:
 
 <ul>
 <li>
 
 Operationalizing Research
 
 : Collaborate with researchers to transition models from experimental checkpoints to production-ready systems. Establish scalable patterns for large-scale training, rapid experimentation, and deployment of new architectures.
 </li>
 <li>
 
 Optimizing Model Performance
 
 : Profile and enhance model inference for latency and throughput using techniques like quantization, pruning, distillation, and architectural refinements to ensure cost-effective scalability.
 </li>
 <li>
 
 Model Acceleration
 
 : Apply optimization techniques (e.g., TensorRT, ONNX, vLLM) to accelerate multimodal models, including video diffusion, large language models (LLMs), and speech models.
 </li>
 <li>
 
 Designing Data Pipelines
 
 : Build efficient pipelines for video data ingestion, preprocessing, and training at
 
 petabyte scale
 
 using tools like Dagster and Ray.
 </li>
 <li>
 
 Evaluating and Iterating
 
 : Develop evaluation frameworks to measure model quality, establish benchmarks, and guide continuous improvement of model capabilities.
 </li>
 </ul>
 
 
 What We&rsquo;re Looking For
 
 
 
 We&rsquo;re seeking candidates with a strong foundation in AI research and production engineering. The ideal candidate will have:
 
 <ul>
 <li>
 
 Production ML Experience
 
 : Proven track record of deploying ML models to production, with a deep understanding of common failure modes (e.g., resource contention, OOMs, batch optimization) and how to address them.
 </li>
 <li>
 
 Deep Learning Expertise
 
 : Strong knowledge of PyTorch and modern ML architectures, with experience training and optimizing large models (e.g., transformers, diffusion models).
 </li>
 <li>
 
 Systems Proficiency
 
 : Comfort working with GPUs, debugging CUDA issues, and profiling model workloads to identify compute or memory bottlenecks.
 </li>
 <li>
 
 Data Engineering Skills
 
 : Experience building scalable data pipelines for high-bandwidth media processing and training workflows.
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Experience with
 
 video or audio models
 
 in research or production settings.
 </li>
 <li>
 Familiarity with
 
 low-level optimization
 
 (e.g., CUDA kernels, Triton, custom operators).
 </li>
 <li>
 Knowledge of
 
 real-time ML systems
 
 and latency-critical inference.
 </li>
 <li>
 Prior work with
 
 model compression techniques
 
 (quantization, distillation, pruning).
 </li>
 </ul>
 
 
 Why Join Us?
 
 
 <ul>
 <li>
 
 Impactful Work
 
 : Your contributions will directly shape the future of real-time AI avatars, advancing cutting-edge research into products that touch millions of lives.
 </li>
 <li>
 
 World-Class Team
 
 : Collaborate with some of the brightest minds in AI, including researchers and engineers from top institutions and companies.
 </li>
 <li>
 
 Growth Opportunities
 
 : Be part of a fast-growing startup with significant funding and a clear vision for the future.
 </li>
 <li>
 
 In-Person Collaboration
 
 : Work alongside your teammates in our vibrant
 
 Seattle HQ
 
 , fostering creativity and innovation through daily collaboration.
 </li>
 </ul>
 
 
 How to Apply
 
 
 
 If you&rsquo;re excited about the opportunity to work on
 
 multimodal AI models
 
 and help bring groundbreaking research to life, we&rsquo;d love to hear from you! Apply now to join a team shaping the future of AI.
 
</div>

Artificial Intelligence Researcher

From our origins in iPhone keyboard input, the Input Experience NLP team has expanded to a broad charter: improve the user experience with robust language understanding and personalized text composition, across languages and Apple platforms. We build the ML models that underlie Summarization, Smart Reply, Writing Tools, and other features deeply integrated into Apple products. Generative AI is a transformative technology that we have only just begun to incorporate into our digital lives, to help everyday people digest the deluge of information they receive and express themselves more clearly. On our team, you will help build the future and have a voice in the shape it takes. 
 
We are looking for a Machine Learning Engineer to develop the next generation of our ML models, so that they better serve the full range of our customers, across languages, writing styles, and other personal context, in a privacy-preserving way. You will build, run, and refine the training and evaluation pipelines that define our slice of Apple Intelligence, driving the focused experimentation and iteration that makes the user experience magical. You will join an ambitious, organized, and collaborative team. We&rsquo;re in a unique position to integrate the latest innovations from the ML community and work on features that reach everyday users, including your family and friends. You&rsquo;ll work closely with teams across Apple, collaborating on human interfaces, user studies, internationalization, ML technologies, system integration, and more. 
 
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something-you&rsquo;ll add something. 
 
Description 
 
As a Machine Learning Engineer on our team, you will enable next-generation AI applications by building toolkits and workflows that scale to increasingly sophisticated modeling tasks. You will design the abstractions and implement the algorithms that facilitate efficient data synthesis, data curation, prompt engineering, and model evaluation. You will contribute to a company-wide effort to build robust modeling pipelines that optimize our ability to iterate rapidly and continuously deliver improvements to our customers. Finally, you will help define and refine new features that expand both the depth of Apple Intelligence&rsquo;s capabilities and the breadth of its support for the full spectrum of Apple customers&quot;,&quot;responsibilities&quot;:&quot;Development and maintenance of data and model pipelines that scale to deployment in production 
 
Building toolkits for iterating on model quality via data synthesis and prompt engineering 
 
Definition of robust automated evaluation mechanisms to facilitate hillclimbing on model quality 
 
Failure analysis from user feedback to understand shortcomings of our models and evaluation data 
 
Research into state-of-the-art techniques for improving model quality and robustness 
 
Implementation of experiments and simulations to assess the value of model changes 
 
Preferred Qualifications 
 
Familiarity with LLMs, such as SFT, RHLF, prompt engineering, data synthesis, automatic evaluation, and RAG 
 
Expertise in MLOps and a passion for software quality, based on CI/CD principles 
 
Excellent written and verbal communication skills 
 
Background in linguistics, fluency in multiple languages, or a passion for scaling NLP features for global audiences 
 
History of developing Python packages and supporting users and other teams 
 
Minimum Qualifications 
 
MS or PhD in Computer Science or related field with at least 2 years of industry experience 
 
Strong Python programming skills, with experience developing production-quality Python modules 
 
Experience building and maintaining model pipelines end-to-end, from data curation to evaluation 
 
Solid background in machine learning, data science, natural language processing, or statistics 
 
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.

Machine Learning Engineer, Natural Language Generation

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