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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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BS degree or equivalent experience in Systems Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering. MS degree or equivalent experience in Systems Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Interface with Data Engineering and Product Development teams for the deployment of high-performing and maintainable Deep Learning and Large Language Models. Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
$130,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficient in at least three of the following: applied mathematics, physics, electrical engineering, software design, signal processing, image processing, machine learning, generative AI, reinforcement learning, numerical analysis, statistics.
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In-depth knowledge of deep learning learning algorithms especially for NLP and LLM. Ph. D. or M.S. degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or related fields.
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Experience in structural health monitoring (SHM), non-destructive evaluation (NDE), and non-invasive testing,+ Experience in electrical measurements, building of complex experimental setups, and sensor development,+ Experience in advanced signal processing, including machine learning,+ Proficiency in software development using Python, MATLAB, and LabVIEW,+ Experience in modeling & simulation studies using COMSOL,+ Ability to plan and organize assignments to meet project deliverables.
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Software Engineer, Computer Vision/Deep Learning Bellevue, Washington, United States Mountain View, California, United States Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they're going.
$158,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Foundation in electrical engineering principles including basic circuit design, signal, and power distribution, transmission line theory, EMI and EMC, etc. Applicants familiar with thermal and mechanical engineering principles will be highly valued as many of the electrical systems will interface with mechanical counterparts such as actuation and propulsion systems.
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As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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This position is part of a team that specializes in electrical engineering and assists in the hydrocarbon, water, pharmaceutical, food and beverage and renewable energy markets. As an Electrical Engineer Intern , you primarily focus on developing and learning fundamental concepts, practices and procedures within an overall project team and learning about your field of specialization.
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Proficiency with a deep learning framework such as PyTorch, TensorFlow, or Keras and and/or natural language processing using NLTK, spaCy, Gensim, etc. Apply your advanced understanding of machine learning principles, including advanced analytics tools, applied mathematics, ML and Deep Learning frameworks and libraries, and ML techniques to design, build and support machine learning to achieve high quality generative AI user experiences.
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We’re looking for a strategic thinker who has a strong product and technical acumen to lead our Applied AI Research team and shape the product and business in the coming years via the cutting edge advancements in AI. You’ll be managing a talented team of AI Researchers specialized in generative models and deep learning and will report directly to the VP of Engineering.
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Should have a record of academic excellence, including demonstrated experience in most of the following areas:Applied Mathematics: differential equations, linear algebra, numerical analysis, and continuous or discrete optimization;Engineering: controls, estimation theory, digital signal processing, and machine learning;Scientific Computing: software design, algorithm implementation, and software analysis, testing, and optimization;Probability: statistics and random processes.
$80,900 - $164,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc. Expertise in building deep-learning models in PyTorch, JAX, or TensorFlow. Dive into internals of open-source deep learning frameworks and enhance their functionality.
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deep learning electrical engineering jobs Company: Apple
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One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
When Rage Applying Strikes: How to Identify Unserious Candidates
As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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In today's competitive job market, writing quality job ads is critical for attracting top talent to your organization. While networking and candidate referrals are prime real estate for finding qualified candidates, nothing beats the tried-and-true method of writing an extraordinary job ad. But while writing a great job ad is the first step, what's more important is increasing visibility. You could have the most detailed, well-written ad on the internet, but if no one sees it, then you are wasting time (and potentially money!). Employers often believe that job boards are the root of the problem, but you can learn how to increase job ad exposure by tweaking a few steps of your recruitment process.
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Building a Candidate Pipeline Through Internships
Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
Hiring Transparency
Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.
Recruitment strategies that are weird, but actually work
In the current candidate-driven job market, recruiters are looking for unique ways to attract talent. Some have resorted to even (dare we say it?) recruitment strategies on the border of weird and wacky. What can we learn from the unusual recruitment tactics that are being used and actually getting results? Here’s a rundown of some unique recruitment strategies that actually work.