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YO IT Consulting

<div>
 
 Job Title:
 
 AI/ML Engineer
 
 
 
 Job Type:
 
 Full-Time
 
 
 
 Job Summary
 
 
 
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
 </li>
 <li>
 Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
 </li>
 <li>
 Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
 </li>
 <li>
 Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
 </li>
 <li>
 Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
 </li>
 <li>
 Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
 </li>
 <li>
 Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Required Skills And Qualifications
 
 
 
 <ul>
 <li>
 Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
 </li>
 <li>
 Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
 </li>
 <li>
 Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
 </li>
 <li>
 Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
 </li>
 <li>
 Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
 </li>
 <li>
 Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
 </li>
 <li>
 Exceptional written and verbal communication skills for effective collaboration and documentation.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
 </li>
 <li>
 Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
 </li>
 <li>
 Prior exposure to government or highly regulated cloud environments and compliance standards.
 </li>
 </ul>
</div>

AI/ML Engineer - Remote

DigitalOcean

<div><div>Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together&mdash;while learning, having fun, and making a profound difference for the dreamers and builders in the world.</div><h2 class="jobSectionHeader">
We are looking for a Manager, Customer Success Engineering (AI &amp; Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.</h2>

As a Manager, CSE (AI &amp; Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering &quot;white-glove&quot; experiences for strategic customers.<h2 class="jobSectionHeader"> 

What You'll Do:</h2>

Team Leadership &amp; Development
<ul>
<li>Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth</li>
<li>Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.</li>
<li>Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.</li>
<li>Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.</li>
<li>Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.</li> 
</ul>
Strategic Customer Support 
<ul>
<li>Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.</li>
<li>Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.</li>
<li>Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.</li>
<li>Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.</li>
</ul>
Technical &amp; Cross-Functional Operations
<ul>
<li>Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.</li>
<li>Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product &mdash; including Jira escalation routing, Sev1 bridge management, and post-incident documentation.</li>
<li> Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content &mdash; treating documentation infrastructure as a core operational lever for team scalability.</li>
<li>Contribute to the vision for AI and automation within support&mdash;building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.</li>
<li>Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.</li>
</ul><h3 class="jobSectionHeader">Key Metrics:</h3>
<ul><li>Customer Satisfaction (CSAT) for strategic accounts</li>
<li>Time to Response and Resolution (TTR) for strategic customers</li>
<li>Tier 1 resolution rate vs. escalation rate</li>
<li>Time-to-escalation and engineering handoff SLA adherence</li>
<li>SLA adherence and escalation response times</li>
<li>Support productivity and quality (QA scores)</li>
<li>Post-incident documentation completion rate</li>
</ul><h2 class="jobSectionHeader">What You'll Add to DigitalOcean:</h2>
<ul><li>Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.</li>
<li>Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.</li>
<li>Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.</li>
<li>Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.</li>
<li>Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.</li>
<li>Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.</li>
</ul>
Preferred Qualifications:
<ul>
<li>Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).</li>
<li>Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.</li>
<li>Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field.</li>
<li>ITIL or equivalent service management certification</li>
</ul><h2 class="jobSectionHeader">Compensation Range:</h2>
<ul><li>$125,000 - $153,000</li>
</ul>
<ul><li>This is a remote role</li></ul>

JR: 2026-7692

#LI-Remote<div><h2 class="jobSectionHeader">
Why You'll Like Working for DigitalOcean</h2>
<ul><li>We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.</li>
<li>We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.</li>
<li>We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.</li>
<li>We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.</li>
<li>DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.</li>
</ul>
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.</div></div>

Manager, Customer Success Engineering

Apple

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&rsquo;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. 
 
&quot;,&quot;responsibilities&quot;:&quot;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. 
 
Preferred Qualifications 
 
3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality. 
 
Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc). 
 
Strong problem-solving and communication skills. 
 
Experience of multimodal large language model or image/video generation model training is a plus. 
 
Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas. 
 
Minimum Qualifications 
 
Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning. 
 
Deep understanding in multi-modal foundation models. 
 
Staying on top of emerging trends in generative AI and multi-modal LLM. 
 
Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax. 
 
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.

AIML - Sr Machine Learning Engineer, Data and ML Innovation

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide! Prototype, scale, and optimize algorithm improvements. Build robust, large-scale personalized recommender systems for Apps, Games, Videos, Podcasts and Fitness. See your work touch the lives of billions of Apple users worldwide. 
 
The Apple Services Engineering team is one of the most exciting examples of Apple&rsquo;s long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Fitness+. And we do it on a massive scale, meeting Apple&rsquo;s high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. 
 
Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple&rsquo;s unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple&rsquo;s privacy policy, one of Apple&rsquo;s core values. Although services are a bigger part of Apple&rsquo;s business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here. 
 
Description 
 
We are looking for an exceptional Machine Learning Engineer to help us build and scale personalization systems using the latest advances in machine learning. With your engineering expertise, we want to develop robust, high-performance solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple&rsquo;s truly incredible global scale.&quot;,&quot;responsibilities&quot;:&quot;Design, build, and maintain scalable machine learning pipelines and infrastructure for training and serving personalization models. 
 
Partner closely with ML researchers to transition prototype models into highly optimized, production-ready systems. 
 
Optimize model inference for low latency and high throughput to meet the rigorous demands of Apple&rsquo;s global user base. 
 
Implement robust monitoring, A/B testing infrastructure, and evaluation frameworks to ensure model quality and reliability in production. 
 
Ship production-quality code and drive engineering best practices, system architecture, and code quality within the team. 
 
Preferred Qualifications 
 
Master&rsquo;s degree in Computer Science, Software Engineering, Mathematics, or a related field; OR equivalent practical industry experience. 
 
Industry experience specifically focused on MLOps, recommendation systems, or search ranking infrastructure. 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree in Computer Science, Software Engineering, Mathematics, or a related technical field. 
 
2+ years of relevant work experience. 
 
Strong software engineering fundamentals and technical competence in production-quality software development. 
 
Real-world experience with building, scaling, and deploying recommendation systems or large-scale ML models. 
 
Proven grasp of the open-source Python AI/ML tech stack, including PyTorch, scikit-learn, and numpy-scipy-pandas. 
 
Solid understanding of machine learning algorithms, design patterns, and tools, including deep learning and generative AI. 
 
Proficiency with big data technologies, data processing pipelines, and distributed computing (e.g., Spark, Hadoop, Kafka). 
 
Experience with ML infrastructure, model optimization, and serving models at scale with low latency. 
 
Strong written &amp; oral communication skills, with a collaborative mindset. 
 
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, Apple Services Engineering

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

We&rsquo;re starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our team in the Video Computer Vision group and help us enable that potential for realtime human understanding on Apple devices. The Video Computer Vision org has pioneered human-centric real-time features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life. 
 
Description 
 
As part of the Video Computer Vision (VCV) team, you will support our ML development and continuously improve our features. Working closely with ML algorithms engineers, data scientists and quality assurance teams, you&rsquo;ll help deploy state-of-the-art computer vision technologies on Apple devices, balancing performance with the compute and power constraints of on-device inference.&quot;,&quot;responsibilities&quot;:&quot;Develop applications and tools for algorithm evaluation, prototyping, and technology demonstrations. 
 
Support teams across Apple by integrating ML and CV components into production systems. 
 
On-device integration of CV/ML algorithms. 
 
Preferred Qualifications 
 
Experience with CoreFoundation, RealityKit and CoreML. 
 
Hands-on experience with CI/CD pipelines and practices. 
 
Experience with live camera streaming applications: Understanding of real-time video pipelines, image transformations, and rendering loops. 
 
Familiarity with common computer vision techniques (e.g., object detection, segmentation, tracking, pose estimation), sequence models for real-time inference and LLMs optimized for on-device performance. 
 
Minimum Qualifications 
 
Bachelor's degree in Computer Science or related discipline, and 2 years relevant industry experience. 
 
Strong foundational knowledge in Computer Science. 
 
Extensive programming experience in Python, Swift, C++. 
 
Experience working with PyTorch. 
 
Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. 
 
Foundational understanding of machine learning: ML algorithms and development pipelines, with the ability to work effectively with ML practitioners and integrate ML components into production systems. 
 
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.

On-Device Machine Learning Integration Engineer

lululemon

Who we are
 
lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people.
 
About this team
 
The Data & AI Security team is responsible for protecting the organization’s most critical data and AI assets while enabling responsible, scalable innovation. We build and operate Data Security Posture Management (DSPM) and AI Security Posture Management (AISPM) capabilities across a complex, global ecosystem. Our work is highly cross-functional, partnering with Data & Analytics, Engineering, Legal, Privacy, and GRC teams to embed security by design while keeping the organization fast, compliant, and resilient. Our focus is on visibility, prevention, and remediation at scale, balancing strong security controls with minimum business friction.
 
The Senior Cybersecurity Engineer is responsible for securing the organization’s AI ecosystem by discovering, assessing, and mitigating risks associated with AI models, data usage, model lifecycle, and AI-driven workflows. This role partners closely with Data Governance, Platform Engineering, and Security Architecture to enable safe and scalable AI adoption while ensuring regulatory, privacy, and corporate policy alignment.
 
Core responsibilities
 
As a Senior Cybersecurity Engineer, you will lead complex security engineering initiatives, designing and implementing security controls, platforms, and solutions that protect critical systems at scale. You will build and operate enterprise security capabilities such as centralized authentication, security enforcement mechanisms, and security automation, while applying secure coding practices and rigorous testing and validation. You will partner closely with engineering teams to embed security into system design and delivery, drive improvements to security quality and reliability, and mentor junior engineers through hands-on technical leadership and knowledge sharing.
 
Select responsibilities include: 
*
 <ul>
<li>Build enterprise security systems implementing centralized authentication, security platforms, and organization-wide controls</li>
<li>Lead comprehensive threat modeling and security assessments for complex systems, evaluating attacker behaviour across integrations and influencing secure design decisions early in the development lifecycle</li>
<li>Own end-to-end response for complex security incidents, driving deep root cause analysis and delivering coordinated long-term improvements to detection, prevention, and security monitoring capabilities</li>
<li>Develop advanced security code, tools, and libraries including security automation platforms, scanners and detectors, security testing systems, and security SDKs</li>
<li>Establish security code standards defining secure coding practices, code review requirements, and implementation quality</li>
</ul>
Qualifications
 <ul>
<li>Bachelor’s degree in Computer Science, Cybersecurity, or related field; security certification strongly preferred</li>
<li>6-10 years of experience leading security engineering initiatives, establishing security standards and practices, and building security systems at scale, or equivalent</li>
<li>Hands-on experience securing data used by AI systems, including data discovery, classification, access governance, and usage monitoring across cloud data platforms, feature stores, and AI pipelines</li>
<li>Experience securing AI and analytics workloads in modern cloud environments, including identity and access controls, service-to-service authentication, secrets management, and policy enforcement across platforms supporting AI/ML development and inference (e.g., cloud data platforms, ML platforms, containerized services)</li>
<li>Proven experience implementing enterprise security controls and building security infrastructure including centralized authentication, authorization services, and security policy enforcement systems at scale</li>
<li>Track record of writing complex security systems including security platforms and SDKs; experience establishing security code review practices, security checklists, and security development frameworks</li>
<li>Demonstrated ability to lead advanced threat modeling for complex systems, anticipating sophisticated adversarial behaviour; experience owning investigation and resolution of complex security incidents with deep root cause analysis</li>
<li>Familiarity with DSPM, DLP, or data governance tooling applied to AI use cases is strongly preferred</li>
</ul>
Must haves
 <ul>
<li>Acknowledge the presence of choice in every moment and take personal responsibility for your life.</li>
<li>Possess an entrepreneurial spirit and continuously innovate to achieve great results.</li>
<li>Communicate with honesty and kindness and create the space for others to do the same.</li>
<li>Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.</li>
<li>Foster connection by putting people first and building trusting relationships.</li>
<li>Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously.</li>
</ul>
Please Note: 
Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time for this role.
 
Compensation and benefits package
 
lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. The typical hiring range for this position is from $147,300 - $193,300 annually; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program, subject to program eligibility requirements.
 
At lululemon, investing in our people is a top priority. We believe that when life works, work works. We strive to be the place where inclusive leaders come to develop and enable all to be well. Recognizing our teams for their performance and dedication, other components of our total rewards offerings include support of career development, wellbeing, and personal growth:
 <ul>
<li>Extended health and dental benefits, and mental health plans</li>
<li>Paid time off</li>
<li>Savings and retirement plan matching</li>
<li>Generous employee discount</li>
<li>Fitness & yoga classes</li>
<li>Parenthood top-up</li>
<li>Extensive catalog of development course offerings</li>
<li>People networks, mentorship programs, and leadership series (to name a few)</li>
</ul>
Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.
 
Workplace arrangement
 
This role is classified as In-Person under our SSC Workplace Policy:
 
In-person collaboration and/or office-based work is necessary or important for the role. Work is mainly performed onsite, 4-5 days per week depending on role requirements.
 
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Senior Cybersecurity Engineer - Data & AI Security

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