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The Machine Learning Engineer role requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks like Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments, and also being part of customer success teams.
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We’re looking for a talented Machine Learning Engineer to join Procore’s Product & Technology Team. Procore software solutions aim to improve the lives of everyone in construction and the people within Product & Technology are the driving force behind our innovative, top-rated global platform.
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If you've used Disney+, Peacock, or other top streaming platforms, you've already benefited from Conviva's technology.
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Utilize Infrastructure as Code (IaC) tools, such as Terraform or AWS CloudFormation, to automate the provisioning and management of cloud resources for machine learning. Our Opportunity:Chewy is looking for a Machine Learning Engineer III to join our Merchandising Data Science Team. In this role, you will combine an understanding of machine learning, advanced data analysis, statistical testing, and software development.
$234,500 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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3+ years supporting the development and deploying machine learning & AI models into production and ability to work across structured, semi-structured and unstructured data. Experience working with cloud data warehouses (Snowflake, Google BigQuery, AWS Redshift, Microsoft Synapse)required.
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6+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions. Extensive experience with Python Machine Learning toolsets (Tensorflow, PyTorch, Scikit-learn, Numpy, Pandas.
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Industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in their technical domain area (e.g., NLP, RESUME, etc.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Evaluate and recommend new tools, technologies, and best practices for machine learning development and deployment. Keep up-to-date with the latest advancements in machine learning and artificial intelligence to stay current on emerging techniques and trends.
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Altana provides the world’s only dynamic, intelligent map of the global supply chain - the Altana Atlas - using AI and machine learning models to connect with and learn from massive sets of public and private data.
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Massachusetts General Hospital (MGH) Department of Neurology and Harvard Medical School (HMS) is seeking a signal processing and machine learning post-doctoral fellow for a full-time position in the Gupta Lab. The fellow will be applying diverse methodologies to uncover information in multimodal data collected from individuals with common and rare neurodegenerative diseases.
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10 + years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions. You are curious, always learning, and keep a close eye on latest developments in the fields of Machine Learning and Artificial Intelligence.
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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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PhD/MS in computer science, statistics, or computational science, with a focus on machine learning methods, or a PhD in a related field (e.g., computational chemistry or biology) with a strong emphasis in machine learning method development, and 10+ years of relevant experience.
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Partner with scientific experts to evaluate and develop machine learning methods in various scientific domains, with an initial focus on partnering with chemistry and computational chemistry leaders to accelerate and enhance the discovery of small molecule medicines through improvements to the Design-Make-Test-Analyze cycle.
$282,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago
machine learning jobs Company: Wendy's in AK, Hawaii
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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).