deep learning engineer

Skild AI

<div>
 
 Company Overview
 
 
 At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
 
 
 Position Overview
 
 
 We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
 
 
 Responsibilities
 
 <ul>
 <li>
 Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
 </li>
 <li>
 Design and conduct experiments to train RL models and conduct real-world tests.
 </li>
 <li>
 Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
 </li>
 <li>
 Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
 </li>
 <li>
 Analyze and interpret experimental results, iterating on model design to achieve desired performance.
 </li>
 <li>
 Stay up-to-date with the latest research and advancements in reinforcement learning.
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
 </li>
 <li>
 Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
 </li>
 <li>
 Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
 </li>
 <li>
 Strong background in algorithms, data structures, and software engineering principles.
 </li>
 <li>
 Experience with physics simulation engines and tools for training RL.
 </li>
 <li>
 Deep understanding of state-of-the-art machine learning techniques and models.
 </li>
 <li>
 Extensive industry experience with reinforcement learning and robotic systems.
 </li>
 </ul>
 
 &nbsp;
 
 
 Base Salary Range: $100,000 USD - $300,000 USD
 
</div>

Machine Learning Engineer

SARJ

<div>Sarj.ai is hiring an AI/ML Engineer to train and deploy speech models that power our voice communications platform. We work in Python and PyTorch on GCP. Strong deep learning fundamentals highly appreciated.<h3 class="jobSectionHeader">
What you'll do</h3><ul><li>
Train large-scale speech models (STT/TTS)</li><li>
Work with modern speech architectures and push them to production</li><li>
Build and maintain ML training pipelines for real-time voice processing</li><li>
Develop evaluation frameworks and improve model performance</li><li>
Collaborate with product and engineering to ship AI-powered features</li></ul><h3 class="jobSectionHeader">
What we're looking for</h3><ul><li>
2+ years working with ML in production</li><li>
Strong Python + PyTorch/PyTorch Lightning</li><li>
Understanding of deep learning fundamentals</li><li>
Experience with speech/audio ML is a strong plus</li><li>
Experience with large-scale or distributed training</li><li>
Familiarity with GCP (Vertex AI, Cloud Run, BigQuery)</li></ul></div>

AI Research Engineer

Apple

Would you like to be a part of Apple&rsquo;s AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. 
 
Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING: 
 
Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. 
 
Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. 
 
Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. 
 
Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions. 
 
Preferred Qualifications 
 
Deep understanding of multi-modal foundation models. 
 
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs. 
 
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams. 
 
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.). 
 
Track records of adopting ML to solve cross-disciplinary problems. 
 
Minimum Qualifications 
 
Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning. 
 
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of). 
 
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.&lsquo; 
 
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 $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'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

Openkyber

<div>Job Title: AI / ML Engineer 
Location: Dallas, TX or Memphis, TN Hybrid 
Duration: 6+ Months
Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution and developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills :
<ul><li>Advanced knowledge of Python specifically for machine learning and data science.</li>
<li>Experience with LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, or AutoGen.</li>
<li>Proficiency in cloud services related to ML/AI (e.g., Azure, OpenAI, Hugging Face, AWS, Google Cloud Platform).</li>
<li>Extensive experience in AI/ML development, particularly in NLP, and machine learning domains.</li>
<li>Hands-on experience in developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solutions is essential</li>
<li>Proficiency in designing and maintaining AI/ML solutions that are cost-effective, accurate, and scalable.</li>
<li>Exceptional problem-solving skills and the ability to think analytically.</li>
<li>Strong communication and interpersonal skills, with the aptitude to navigate complex project requirements with clients and stakeholders.</li>
</ul>Nice to have: Certification as an Azure AI Engineer Associate or equivalent credentials is highly advantageous.
Experience with ML/DL frameworks like TensorFlow, Keras, PyTorch, and scikit-learn.
Experience with C# or Java, node.js.
With Regards, OpenKyber 
7525 Mitchell Road, Suite 106, Eden Prairie, MN 55344 
Email ID - hirings@openkyber.com
For applications and inquiries, contact: hirings@openkyber.com</div>

OCI AI Services Engineer

Quantum HR

<div>About Us
Quantum HR is a premier human resources consulting firm dedicated to connecting exceptional talent with leading organizations worldwide. We specialize in providing bespoke recruitment solutions, leveraging deep industry insights and a global network to help companies build high-performing teams by matching them with professionals who truly fit their needs and culture. 
 
About the Role
We are hiring a Machine Learning Engineer to design, build, and deploy advanced ML models powering Digified&rsquo;s digital identity verification and contracting platforms. 
You will work on real-world, high-impact problems in computer vision, biometrics, OCR, fraud detection, and NLP, delivering production-grade ML systems integrated into APIs and enterprise workflows.
This is a hands-on engineering role focused on taking models from research to scalable, secure, and compliant production environments. 
 
Key Responsibilities 
<ul><li>
Develop and optimize ML models for face recognition, liveness detection, OCR, fraud detection, and NLP-based document understanding
</li><li>Build and maintain production-grade ML pipelines and APIs for real-time inference
</li><li>Deploy and scale models using MLOps best practices (CI/CD, versioning, monitoring, retraining)
</li><li>Optimize model performance for latency, accuracy, and reliability in production environments
</li><li>Design and manage high-quality datasets with proper annotation and data governance
</li><li>Monitor model performance (drift, accuracy, false acceptance/rejection rates)
</li><li>Collaborate with backend, mobile, DevOps, and product teams to integrate ML systems
</li><li>Ensure secure, compliant ML practices aligned with regulatory and data privacy standards
</li><li>Conduct research and propose improvements in model architectures and system performance</li></ul> 

Requirements 
<ul><li>
3&ndash;7 years of experience in Machine Learning, Deep Learning, or Computer Vision
</li><li>Strong Python programming skills
</li><li>Experience with PyTorch and/or TensorFlow/Keras
</li><li>Strong background in at least one of: Computer Vision, NLP, or Fraud Detection
</li><li>Experience with ML deployment (FastAPI, Flask, Docker, Kubernetes)
</li><li>Understanding of MLOps principles (model versioning, monitoring, retraining pipelines)
</li><li>Solid foundation in mathematics (linear algebra, probability, statistics)
</li><li>Experience working with production ML systems 
 
Nice to Have 
</li><li>
Experience with face recognition, OCR, or liveness detection systems
</li><li>Exposure to Vision Transformers, Siamese Networks, CRNNs, or LLM-based systems
</li><li>Experience with distributed training or GPU acceleration
</li><li>Familiarity with MLflow or experiment tracking tools
</li><li>Knowledge of identity standards (FIDO, NIST 800-63-3)
</li><li>Background in fintech, regtech, or anti-fraud systems
</li><li>Experience with trust &amp; safety or government-grade systems</li></ul> 

Benefits 
<ul><li>
Work on cutting-edge ML systems in digital identity and fraud prevention
</li><li>High-impact role with production ownership from research to deployment
</li><li>Exposure to enterprise-grade AI systems used in regulated environments
</li><li>Strong engineering culture with cross-functional collaboration
</li><li>Opportunity to work on advanced CV/NLP/biometric systems at scale
</li><li>Career growth in a fast-scaling AI-driven product company</li></ul></div>

ML Engineer

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

Microsoft

<div>Overview<div> 
As an AI Engineer in the Office AI team, you work to enhance Office productivity with AI-driven experiences and services across key applications. The team builds the core platforms and experiences that bring large language models (LLMs) and realtime intelligence into Office apps. These platforms are key components of Microsoft Copilot, combining the power of large language models with enterprise data and native integration with Office apps to streamline productivity, including content generation, navigation, comprehension and more.
We are looking for a creative AI Engineer who will collaborate with software engineers, researchers, and product managers to express product needs as well defined machine learning problems, push the state of the art in LLMs and bring prototypes all the way to planet scale production. You&rsquo;ll build the engineering that makes AI work in production: you will build APIs, platforms and services around AI features; design data pipelines and feedback loops; deploy and finetune state of the art deep learning models; orchestrate prompts and tools; and monitor AI specific signals&mdash;such as drift, hallucinations, safety and cost&mdash;alongside traditional service reliability metrics.
Join us to empower people through AI, bringing cutting edge deep learning into everyday work at scale. At Microsoft, our mission is to empower every person and every organization to achieve more; we show up with a growth mindset, innovate to empower others, and collaborate to realize shared goals. Rooted in respect, integrity, and accountability, we foster an inclusive culture where everyone can thrive. If you are passionate about applying state of the art AI to positively impact millions, this role is for you.
Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</div> 
Responsibilities 
<div><ul><li>
Ship features with PM &amp; Engineering. Co own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets.</li><li>
Generative AI and advanced technologies. Apply knowledge of generative AI, large language models, and modern frameworks to develop intelligent features and automation within the service.</li><li>
Azure platform integration. Deploy, integrate, and manage AI powered solutions within the Azure ecosystem, ensuring security, scalability, and compliance with best practices.</li><li>
Continuous learning and mentoring. Stay current with advances in generative AI and software engineering. Invest time in learning new tools and frameworks, propose improvements to build processes, and share knowledge with colleagues.</li></ul></div> 

Qualifications 
Required Qualifications:<ul><li>
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python<ul><li>
OR equivalent experience.</li></ul></li></ul>
Preferred Qualifications:<div><ul><li>
Master&rsquo;s degree in computer science or related field.</li><li>
1 + years of experience designing and running infrastructure systems that operate globally on a large scale.</li><li>
Experience deploying AI models into production environments and building systems that monitor and retrain models automatically.</li><li>
Passion for mentoring others and contributing to an inclusive team culture.</li><li><div>
Distributed systems and cloud. Familiarity with Azure services, microservices architectures, and distributed storage systems (experience with Cosmos DB or similar is a plus). Ability to design and run fault tolerant infrastructure on a large scale and to implement secure, compliant solutions.</div></li><li><div>
AI and machine learning skills. Handson experience with generative AI or machine learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a solid understanding of LLM concepts, embeddings, and prompt engineering.</div></li></ul></div> 
 
 
Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: 
https://careers.microsoft.com/us/en/us-corporate-pay 
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. 
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.</div>

AI Engineer II

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