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adversarial machine learning engineer

ai engineer (intern)

aiml machine learning engineer data and ml innovation

Apple

<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

Juniper Square

<div>
 
 About Juniper Square
 
 
 
 Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology &ndash; all while contributing as a member of a values-driven organization &ndash; we want to hear from you.
 
 
 Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.
 
 
 
 About Your Role
 
 
 
 We're looking for an AI Engineer Intern to join our team who is excited to help transform the private markets. In this role, you&rsquo;ll work alongside a talented and collaborative team focused on one of our top strategic initiatives - bringing cutting-edge AI innovation to a key product feature that will drive real change in the industry.
 
 
 As an intern, you&rsquo;ll have a hands-on role in designing, building, and testing new AI-driven product features. This isn&rsquo;t a side project - it's a core company priority with executive visibility and high impact. You&rsquo;ll work in close partnership with engineers, product leaders, and mentors who are invested in your growth and success.
 
 
 You&rsquo;ll also gain valuable exposure to company leadership, access to world-class mentorship, and the opportunity to contribute meaningfully to a product that&rsquo;s reshaping how the private markets operate. For the right person, this internship can be a launchpad into a full-time role post-graduation.
 
 
 This opportunity is perfect for someone with a strong engineering foundation who is currently pursuing a master&rsquo;s degree in AI or a related field - and who&rsquo;s excited to innovate, learn fast, and make a real-world impact.
 
 
 
 This is a remote role based in the U.S. or Canada. The internship program runs for 11 weeks at 40 hours per week, with a scheduled start date of Monday, June 8th.
 
 
 
 
 There may be an opportunity to travel to our San Francisco office the final week to participate in the annual Hackathon.
 
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Collaborate with engineers and product managers to design and prototype AI-powered features that directly impact a key product area at the core of our business
 </li>
 <li>
 Contribute to the development, training, and evaluation of machine learning and natural language processing (NLP) models using industry-standard tools and frameworks
 </li>
 <li>
 Work with large and complex datasets - performing data preprocessing, feature engineering, and analysis to support model development
 </li>
 <li>
 Apply foundational machine learning and deep learning techniques to solve real-world problems in the private markets space
 </li>
 <li>
 Assist with integrating AI models into production systems, including testing, validation, and iteration in collaboration with the engineering team
 </li>
 <li>
 Support ongoing research and experimentation efforts, particularly around NLP and large language models (LLMs), to drive innovation in product development
 </li>
 <li>
 Partner closely with engineering, design, and product stakeholders to evaluate the technical feasibility and ensure alignment of proposed AI features with the overall product vision and strategy.
 </li>
 <li>
 Participate in regular team meetings, code reviews, and brainstorming sessions - bringing curiosity, ideas, and technical insight to the table
 </li>
 <li>
 Receive mentorship from experienced AI and engineering leaders, while gaining exposure to company leadership and strategic initiatives
 </li>
 <li>
 Contribute to documentation and knowledge sharing to help scale AI development efforts across the team
 </li>
 <li>
 Take ownership of meaningful projects with the potential to influence long-term company strategy and product direction
 </li>
 <li>
 Embrace a growth mindset - continuously learning new tools, methodologies, and concepts in the rapidly evolving field of AI
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Education &amp; Academic Background
 
 
 
 <ul>
 <li>
 Currently pursuing a Master&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related quantitative field (e.g., Mathematics, Statistics, Physics)
 </li>
 <li>
 Strong academic foundation with relevant coursework in algorithms, data structures, linear algebra, calculus, probability, and statistics
 </li>
 <li>
 Completed or currently enrolled in courses in machine learning, deep learning, NLP, or computer vision (highly desirable)
 
 
 </li>
 </ul>
 
 Technical Skills
 
 
 
 <ul>
 <li>
 Proficient in Python; experience with libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas is a plus
 </li>
 <li>
 Familiarity with data manipulation, preprocessing, and feature engineering techniques
 </li>
 <li>
 Exposure to databases (SQL/NoSQL) and data querying; experience with data visualization tools (e.g., Looker, Tableau, Power BI) is a bonus
 </li>
 <li>
 Understanding of foundational ML algorithms (e.g., regression, decision trees, clustering) and the underlying mathematical concepts
 </li>
 <li>
 A strong grasp of Large Language Model (LLM) mechanisms, including knowledge of sampling strategies, structured output generation, and function-calling capabilities. Hands-on experience with prompt engineering is a strong plus
 </li>
 <li>
 Exposure to cloud platforms (e.g., AWS, GCP) and cloud-based ML services (e.g., Amazon SageMaker, Google AI Platform) is beneficial
 </li>
 <li>
 Basic knowledge of software engineering practices, including version control (Git), Agile development, and API integration (REST, GraphQL)
 
 
 </li>
 </ul>
 
 Soft Skills &amp; Mindset
 
 
 
 <ul>
 <li>
 Strong analytical and problem-solving skills with a high attention to detail
 </li>
 <li>
 Eagerness to learn and apply new AI concepts in a fast-paced, evolving environment
 </li>
 <li>
 Clear and effective communication skills, both written and verbal
 </li>
 <li>
 Collaborative mindset with the ability to contribute meaningfully to team discussions and technical problem-solving
 </li>
 <li>
 Self-starter with curiosity, initiative, and a proactive approach to innovation
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 <ul>
 <li>
 Personal AI/ML projects (e.g., GitHub portfolio)
 </li>
 <li>
 Participation in AI/ML competitions or hackathons
 </li>
 <li>
 Research experience or academic publications in AI-related areas
 </li>
 <li>
 Contributions to open-source projects
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 Compensation for this position includes an hourly rate. The U.S. hourly rate is $50.00 USD and the Canadian hourly rate is $57.00 CAD.
 
 
 #Juniper-US
 
 
 #Juniper-Canada
 
 
 #emergingtalent
 
 
</div>

AI Engineer (Intern)

The Applied Machine Learning team builds production multimodal systems that understand and transform large-scale image, audio, and video content. Our work spans diffusion-based image generation, transcription and diarization, face and object detection, OCR and image description for search, and automated quality control of media pipelines. 
 
We are looking for a Staff Machine Learning Engineer to strengthen our diffusion and video models, adapt small and mid-sized LLMs, and turn our uniquely large corpus of weakly labeled media into a durable product advantage. This is an opportunity to shape the next generation of multimodal experiences end-to-end, from data and models to evaluation and user impact. 
 
Description 
 
The Staff Machine Learning Engineer - Multimodal Generation &amp; Post-Training will be a senior individual contributor on a small, applied ML team focused on production multimodal systems. The role will lead fine-tuning and adaptation of diffusion and emerging video models, as well as post-training of small and medium LLMs for captioning, moderation, and retrieval-friendly descriptions. 
 
The engineer will design data and evaluation workflows that use our large archive of weakly labeled music, podcast, film, TV, and short-form content to drive measurable quality and efficiency improvements. The role includes close collaboration with partner infra teams for model serving and with adjacent product and research groups to bring new capabilities into production. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, or a related technical field. 
 
8+ years of industry experience with production multimodal systems spanning image, audio, and/or video. 
 
Deep expertise with diffusion and video generation techniques (e.g., ControlNet/IP-Adapter, temporal consistency methods, sampling and latency optimization). 
 
Experience with PEFT/QLoRA and post-training approaches such as DPO or related preference-based methods for small and mid-sized LLMs. 
 
Background in ASR/VAD/diarization, OCR, multimodal retrieval, or face recognition with fine-grained temporal alignment. 
 
Familiarity collaborating with infra/platform teams on model serving (e.g., batching strategies, quantization, observability) and translating requirements into reliable production deployments. 
 
Demonstrated ability to define metrics, build evaluation harnesses, and communicate results clearly to cross-functional partners. 
 
Track record of publications, patents, or open-source contributions in relevant areas of machine learning or multimodal modeling. 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience. 
 
5+ years of hands-on industry experience building and shipping machine learning systems to production. 
 
Proven experience training and fine-tuning diffusion or other image/video generative models, including adapter-based methods such as LoRA. 
 
Proficiency in Python and at least one major deep learning framework such as PyTorch. 
 
Experience designing and operating ML pipelines for noisy or weakly labeled data, including offline evaluation and monitoring in production. 
 
Strong software engineering skills, including code quality, experimentation discipline, and debugging/profiling of model performance. 
 
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 $201,300 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.

Staff Machine Learning Engineer, Apple Services Engineering

Are you passionate about Generative AI and excited to work on groundbreaking modeling technologies that will enrich the lives of billions? The Intelligence System Experience (ISE) team within Apple&rsquo;s software organization is a multidisciplinary group operating at the intersection of Multimodal Foundation Models, Efficient and Scalable ML Infrastructure, and Personalized Intelligent Experiences. As a senior machine learning engineer on our team, you will design software systems and algorithms that enable performant, scalable training and inference for Apple&rsquo;s AI-driven experiences across both on-device and server environments. This role also includes opportunities to open source your work. Join our team of highly skilled, impact-focused engineers! 
 
Description 
 
We&rsquo;re seeking strong senior machine learning engineers to help build next-generation tools for large-scale deep learning. You&rsquo;ll join a team focused on accelerating training and inference speed, improving scalability, and advancing Apple&rsquo;s centralized ML platform. Candidates should bring polished coding skills and a passion for machine learning and computational science. We offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities. 
 
In this role, you will develop core components for our scalable ML platform, push the limits of existing training technologies, and create new techniques to overcome system constraints. Your work will be deployed on high-impact tasks across teams building Apple Intelligence products, with opportunities to open-source your contributions. We are especially looking for a PyTorch-focused ML efficiency expert to optimize training and inference performance, improve distributed training throughput, and drive system-level efficiency for large-scale models. If you have deep experience with PyTorch internals and high-performance ML infrastructure, we&rsquo;d love to hear from you. 
 
Preferred Qualifications 
 
Experience developing model parallel and data parallel training solutions and other training optimizations 
 
Experience with parallel training libraries such as torch.distributed, DeepSpeed, or FairScale 
 
Experience with CUDA-level optimization 
 
Experience building ML models targeting Apple Silicon 
 
Experience building large-scale deep learning infrastructure or platforms for distributed model training 
 
Publication record at Machine Learning conferences such as MLSys, NeurIPS, etc. 
 
Minimum Qualifications 
 
PhD or Master's degree in the area of Computer Science, or equivalent years of industry experience 
 
3+ years working with AI/ML technologies in production or research settings 
 
Strong Python programming skills 
 
Understanding software design principles, and algorithms 
 
Experience with deep learning frameworks, such as PyTorch 
 
Experience building large-scale distributed systems 
 
Familiarity with parallelization algorithms for large model training 
 
Familiarity with recent developments in foundation model architectures 
 
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 Machine Learning Efficiency Engineer - SIML, ISE

RedCloud Consulting

<div>RedCloud Consulting is a business and IT consulting company with local Puget Sound Enterprise and Mid-sized clients. RedCloud seeks a Senior Data Engineer to support immediate client operations. Seattle Business Magazine has recognized us, ranked #1 on their &quot;Best Companies to Work for in Washington&quot; for Mid-Sized Businesses list, awarded #1 Fastest Growing Company in Washington by Puget Sound Business Journal, and named on the Inc. 500/5000 list. 
 
Overview: 
This role supports large-scale, fast-evolving advertising systems where priorities change rapidly and perfect requirements are rare. The Senior Data Engineer will design, build, and operate massive-scale data pipelines that power bidding, targeting, experimentation, and measurement. Ideal candidates are deeply technical, strong owners, and able to deliver durable solutions under ambiguity and infrastructure constraints. 
Build and operate high-reliability, high-scale data systems that enable real-time advertising decisioning and analytics. This engineer will own critical pipelines end-to-end, reduce recurring operational pain, increase efficiency, and drive innovation in an ads ecosystem where scale, speed, and correctness are essential. 
Team works on Pacific Time. Preference for Seattle-local candidates. 
 
Responsibilities include but are not limited to:
<ul><li>Design, build, and maintain large-scale data pipelines supporting bidding, targeting, experimentation, and measurement.</li>
<li>Optimize workflows under real-world constraints&mdash;sampling limits, narrow data windows, service ceilings, and high-throughput requirements.</li>
<li>Ensure reliability, performance, and cost-efficiency across batch and streaming workloads.</li>
<li>Build scalable solutions that deliver value today while creating a path for evolution over time.</li>
<li>Own pipelines end-to-end, from design to deployment to maintenance.</li>
<li>Diagnose, resolve, and eliminate recurring issues to strengthen system stability.</li>
<li>Reduce duplicated workflows, wasted compute, and operational overhead.</li>
<li>Establish engineering best practices around quality, testing, deployment, and observability.</li>
<li>Partner closely with platform teams, infra teams, and other data/ML groups to unblock scaling constraints.
</li><li>Work directly with Data Science, ML Engineering, and Product to deliver features, unblock analysis, and support experimentation.
</li><li>Translate ambiguous requirements into well-structured engineering solutions.</li>
<li>Operate with urgency in an environment where priorities shift quickly.
</li><li>Drive initiatives from zero to one with minimal guidance.
</li><li>Innovate within constraints and deliver solutions that work in the real world&mdash;not just on paper.</li>
</ul>
 
Required Knowledge, Skills, and Abilities:
<ul><li>Deep expertise in at least one major big data ecosystem (e.g., Spark, Flink, EMR, Hadoop-style systems).
</li><li>Strong proficiency with distributed compute frameworks (Spark strongly preferred).
</li><li>Experience building and operating pipelines at massive scale, including challenges like:
<ul><li>Streaming ingestion</li>
<li>High-volume batch ETL</li>
<li>Strict SLAs or constrained windows</li>
<li>Sampling and stateful processing</li>
</ul></li><li>Hands-on experience with cloud-based data infrastructure (AWS or equivalent), including:
<ul><li>Object storage (e.g., S3)</li>
<li>Data lake formats (Iceberg/Hudi-style tables)</li>
<li>SQL engines (Redshift, Athena, Snowflake, etc.)</li>
<li>Streaming frameworks (Kinesis or Kafka-style systems)</li>
</ul></li><li>Strong coding skills in Python, Java, and/or Scala.
</li><li>Experience with infrastructure-as-code frameworks (e.g., Terraform).
</li><li>Strong engineering discipline with Git, CI/CD, testing frameworks, and automated deployment processes.</li>
<li>Exposure to advertising, experimentation, or ML-driven systems is highly beneficial:
<ul><li>Real-time bidding / auction systems</li>
<li>Feature pipelines or feature stores</li>
<li>Measurement and attribution systems</li>
<li>Online/offline ML model pipelines</li>
</ul></li><li>High ownership mindset: &ldquo;I will figure it out and ship it.&rdquo;
</li><li>Bias for action and comfort moving quickly with incomplete requirements.
</li><li>Strong ability to operate independently and deliver end-to-end solutions.
</li><li>Adaptability in dynamic environments with fast-changing priorities.
</li><li>Curiosity, learning speed, and enjoyment of solving hard scaling problems.</li>
</ul>Technology &amp; Tooling Experience:
<ul><li>Cloud &amp; Compute: AWS, Kubernetes, Lambda, Step Functions
</li><li>Data Lake: S3, Iceberg/Hudi-like table formats
</li><li>Analytics: Redshift, Athena, EMR/Spark
</li><li>Batch &amp; Orchestration: Spark, Airflow-style orchestration
</li><li>ML/Modeling: SageMaker or custom ML platforms
</li><li>Languages: Python, Java, Scala, SQL
</li><li>Infra &amp; DevOps: Terraform, Git, CI/CD</li>
</ul>
 
Compensation range for position is $ 200,000 &ndash; 280,000 DOE.
 
Benefits and bonus information can be found at https://www.redcloudconsulting.com/careers
 
RedCloud requires employees have the legal ability to work in the United States during their employment period. During onboarding, proof of eligibility to work in the United States will be requested. RedCloud does not provide visa sponsorship. 
 
About Us: 
RedCloud is a boutique, business and technology consulting firm providing local companies with expert-level support for over two decades. Whether it&rsquo;s to solve a specific business challenge or to provide additional support for an ambitious project, we can help bring even the most visionary endeavors to fruition. 
 
Anchored by a foundation of &quot;integrity-based consulting&quot;, the RedCloud team of subject matter experts collaborate closely with clients to develop and implement high-level solutions, bringing stability, growth, and innovation together for long-term success. We provide a broad array of business and technology consulting services through RedCloud&rsquo;s core practices: Data &amp; AI, Delivery Excellence, Digital Solutions, Marketing &amp; Sales, Privacy, Security, and Strategy &amp; Transformation. 
 
 
 
Visit http://www.redcloudconsulting.com/ for more info.
 
#LI-Remote</div>

Sr. Data Engineer - Monetization & Experimentation

MORSE Corp

<div>
 
 MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding
 
 cutting-edge
 
 
 technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.
 
 
 &nbsp;
 
 
 
 
 We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE&rsquo;s AI &amp; ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE&rsquo;s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments.
 
 
 &nbsp;
 
 
 
 Responsibilities:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.&nbsp;
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Use MLOps tools for efficient experiment tracking, data management, and reproducibility
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Write robust, efficient, and maintainable code
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models
 
 
 &nbsp;
 
 
 </li>
 </ul>
 
 Skills and Requirements:
 
 
 &nbsp;
 
 <ul>
 <li>
 
 US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proven experience testing and validating the performance of AI technologies in real-world applications
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proficiency in Python
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with cloud platforms (AWS and Azure)
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with Docker
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Exceptional communication skills and the ability to work well with customers
 
 
 &nbsp;
 
 </li>
 </ul>
 <ul>
 <li>
 
 Understanding of Department of Defense requirements and standards is a plus
 
 
 &nbsp;
 
 </li>
 </ul>
 
 
 &nbsp;
 
 
 
 
 
 
 &nbsp;
 
 
 
 
 &nbsp;
 
 
 
 MORSE Corp&rsquo;s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.Employees also receive 10 paid holidays per year. MORSE maintains an &ldquo;open&rdquo; leave policy that does not restrict exempt, regular full-time employees to a specific&nbsp;number of paid sick or vacation days. However, this policy is not an &ldquo;unlimited&rdquo; paid leave policy.&nbsp;
 
 
 Compensation: $90,000 USD - $210,000 USD
 
 
 The team at MORSE takes pride in being the smart team that is easy to work with. We focus on steady, long-term success while maintaining a collaborative, enjoyable work experience for our employees. Our team values work-life balance through flexibility and other programs, along with a comprehensive benefits package for employees and families. For more information, please visit www.morsecorp.com.
 
 
 
 &nbsp;
 
 
</div>

Machine Learning Engineer

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>Experience collaborating with other engineers and non-tech stakeholders, both to meet short-term goals and to create long-term partnerships. 
<li>
</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.</div>

Software Engineer II - Earner Incentive

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