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We’re looking for a Machine Learning Engineer who will build out and design machine learning infrastructure for a team of data & remote sensing scientists, working collaboratively with the Analytics and Software teams to deliver data-driven products and solutions.
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Our tenant is a strong cross-domain team to deliver E2E solutions covering tech areas ranging from machine learning, big data, microservices to data visualization. Our team is seeking a senior software engineer who will be a core team member for our advertising data platform engineering group.
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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. Senior Machine Learning Engineer At Altana Location: Boston, MA, Brooklyn, NY, San Francisco, CA, Washington, D.C., Remote, London, England.
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6+ years of experience in machine learning and AI, preferably with exposure to animation, gaming, or visual effects industries. Lead the development and implementation of AI and machine learning technologies to revolutionize animation processes, from pre-production to post-production.
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Responsibilities Implement real-time cutting edge algorithms in signal processing, computer vision, and machine learning. Propose, prototype, and deliver new methods and machine learning models to multiple production environments including Linux and mobile (iOS, Android.
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Experience working with Sagemaker, Tensorflow, Pytorch, Triton, Spark, or equivalent large-scale distributed Machine Learning technologies on a modern containerized deployment stack using Kubernetes, Spinnaker, and other technologies.
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We are looking for someone who has experience as a machine learning engineer or a software engineer, as we operate at the intersection of those two roles.
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We are looking for an experienced software engineer with machine learning expertise to join us in expanding Moveworks NLU (natural language understanding) and agentic AI capabilities, enabling increasingly magical user experiences and improving Moveworks generative and conversational AI capabilities platform-wide.
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As a Senior Machine Learning Engineer, you will work on a broad set of domains that power a data-driven transformation of our standard business procedures across channels.
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Our stack is constantly evolving but based on a backend foundation of Python, Django, Celery, Airflow, and Kafka; a frontend built in React, Redux, and Mapbox; data stores including PostgreSQL and Elasticsearch; machine learning models hosted in Bedrock and Sagemaker; and with AWS, Pulumi, Terraform, and Kubernetes as our underlying infrastructure.
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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. Experience as a solutions engineer, application engineer, data scientist, senior data analyst or a similar technical role at a fast-growing technology company.
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We’re looking for a self-motivated, highly driven Senior Software Engineer to join our Machine Learning Operations (MLOps) team. As a team, we enable Attentive’s Machine Learning (ML) practice to directly impact Attentive’s AI product suite through the tools to train, inference, and deploy ML models with higher velocity and performance, while maintaining reliability.
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The Search Experience team works with a data-driven culture, formed of Data Scientists building machine learning algorithms, and microservice-based architectures to implement Machine Learning and Large Language Model (LLM) solutions to provide the best value to our learners.
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Machine Learning is at the heart of our customer support, and we are looking for a senior modeler to build high-quality support experiences. 5+ years experience with applied Machine Learning or Deep Learning.
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Progressive career experience as a software developer, data engineer, analytics engineer, or ML engineer. We are looking for a strong ML engineer to build new capabilities in the Revenue Operating System to include Air Cargo demand forecasting and ML-based pricing capabilities.
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machine learning software engineer a plus jobs Title: management engineer in San Francisco, CA
FEATURED BLOG POSTS
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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 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
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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.