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We are looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLM’s at Moveworks. Design, build and optimize scalable machine learning infrastructure to support training, evaluation, and deployment of large language models.
$129,000 - $257,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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A law firm is seeking a highly skilled Machine Learning Technology Specialist to join its team in San Diego, CA. The ideal candidate will be responsible for drafting patent applications, corresponding with patent offices, advising patent litigation teams, and conducting interviews with inventors.
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In depth understanding of Machine Learning / Deep Learning / NLP concepts. Stay updated with the latest industry trends in AI and machine learning, and continuously look for opportunities to apply these advancements to improve the LLM infrastructure.
$144,000 - $270,250 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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How you’ll make an impact: As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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The AI COE is seeking a Senior Data Scientist with experience in Conversational AI, Generative Large Language Models, Natural Language Processing, Machine learning, various deep learning related technologies, predictive and prescriptive analytics.
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Advanced knowledge of math, statistics, multivariate analysis, statistical tests Advanced Python coding skills Experience with one or more machine learning frameworks such as TensorFlow and/or PyTorch Understanding of numerical implementations Understanding of cloud computing Knowledge of data querying knowledge of EMG, EEG, ECG, IMU, CV algorithms Experience with C.
$120,000 - $160,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc.
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We work closely with startups and large companies leading the way in machine learning, hardware acceleration, quantum computing, photonics, and bio tech in Boston, New York, and around the USA, to build teams that will change the technology landscape.
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Senior Machine Learning Engineer (Stoneridge, Inc., Novi, MI): On behalf of an automotive electronic product design and production company and reporting to the VP Fleet Products & Services, will work primarily within the Electronics division and will be responsible for collecting, processing, and developing predictive models in the logistics and transportation vertical.
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We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics.
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Our current backend stack is Python, Rust, TensorRT-LLM, Kubernetes, AWS. You will work on designing and implementing machine learning models that drive our recommendation systems, retrieval algorithms, and classifiers.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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machine learning jobs Company: Salesforce Com
FEATURED BLOG POSTS
Virtual Reality Job Interviews
With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
A Potential TikTok Ban?!
As you may already know, there has been a lot of talk lately about the possibility of a TikTok ban. While this has not yet come to fruition, it's important to consider the implications this could have for businesses and recruiters who rely on TikTok as a platform to market their brand, recruit new talent, and connect with their audience.
The Effects of Workplace Racism and Sexism
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.
How to Increase Job Ad Exposure
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.
How to Navigate Hiring Out of State
The job market has shifted significantly in recent years. The accelerated adoption of technology has not only pushed many companies into remote working arrangements but also increased the availability of supporting tools and technologies (i.e., video conferencing and collaboration software).
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.