Remote ML Engineer: Scalable DL & Production Models
Diligent Tec, Inc
A technology solutions company is seeking experienced Machine Learning Engineers (W2 only) to join their fast-growing applied research team. This role offers the opportunity to design and build scalable machine learning services and deploy production-grade models. Candidates must have over 10 years of experience and exceptional communication skills. This position is available for candidates located in the USA and Canada, with a focus on making impactful contributions to large-scale advertising and e-commerce platforms. #J-18808-Ljbffr
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$250k - $295k
...advanced physics and AI to model catastrophic risk at the asset... ...mechanism. The real product is a scalable risk engine, our Stand World Model .... ...Build on and extend scalable ML infrastructure Partner with... ...Knowledge of geospatial, remote sensing, or Earth observation...Remote workFull timeTemporary workH1bWork at officeVisa sponsorshipWork visaFlexible hours$60 - $90 per hour
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...vehicle platforms and product use cases. The Waymo Driver... ...of machine learning (ML) engineers, software engineers,... ...ML algorithms, to model the real world, encompassing... ...the fidelity, scalability, controllability, and... ...role can be performed remote, the specific salary range...Remote workFull time- ...Machine Learning Engineer Location: Helsinki... ...them into robust, production-ready systems. We... ...understanding of scalability best practices. The... ...machine learning models, including data preparation... ...in AI/ML and incorporate cutting... ...company. A flexible remote/hybrid working...Remote workFlexible hours
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...seeking a Senior Machine Learning Engineer to design and deploy advanced models that enhance the analysis of unstructured... ...with engineering teams to build scalable systems, while utilizing expertise... ...significant experience in applied ML engineering. The position offers flexible...Remote jobFlexible hours- ...and enterprises from data and model training through to production deployment, without the cost and... ...of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-... ...and real-world experience Scalable collection, generation, and...Remote workFull time
$70k - $200k
...rapidly improving models through real-field... ...our customers and engineers to deliver value.... ...insights. As an AI/ML Engineer on the... ...deploy them into production. It’s a blend of... ...interpretability . Build scalable evaluation... ...exploring a hybrid or remote option. Why...Remote workFull time- ...an Applied Machine Learning Engineer in San Francisco, CA to bridge... ...cutting-edge research and scalable production applications. You will collaborate... ...optimize, deploy, and scale models like GPT-4 and custom... ...engineering with at least 2 years in ML systems, plus deep knowledge...
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...vehicle platforms and product use cases. The... ...sensors, enabling engineers like you to (1) develop... ..., to (2) develop models and model training... ..., etc. Develop scalable recipes for large... ...~ Experience with ML frameworks like... ...can be performed remote, the specific salary...Remote workFull time- Bright Vision Technologies is seeking an ML Systems Engineer to design, build, and operate high-performance inference platforms for production ML models. This role emphasizes scalable systems engineering, request routing, batching, caching, autoscaling, and observability...Remote job
$203.2k - $348.4k
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$170.1k - $258.3k
...planning research into production‑grade software that can... ...pioneer new approaches to model export, kernel development, and performance engineering so that every cycle on... ...of our on‑vehicle ML inference for ADAS and... ...United States of America; Remote - Washington; Austin, Texas...Remote workFull timeLocal areaWork from homeRelocation packageFlexible hours$128.7k - $261.3k
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...builds an offline ML platform that powers... ...supporting analytics, product intelligence,... ...enables large-scale model training, feature generation... ...a Machine Learning Engineer to join our Offline... ...are reliable, scalable, and efficient.This... ..., Seattle, NYC, Remote CA: $104,100 - $135...Remote workFull timeWork at officeWorldwide$251k - $310k
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$230k - $250k
...seeking a Senior MLOps Engineer to help scale the... ...machine learning-powered products. This is a full-time remote opportunity focused on AWS, Python, ML infrastructure, and... ...focusing exclusively on model development, this... ...machine learning reliable, scalable, and efficient in...Remote workFull timeFlexible hours- ...build state-of-the-art AI models, end to end, from data preparation to production deployment, empowering... ...Sales Machine Learning Engineer who bridges the gap... ...with customers to design scalable ML workflows using best... ...events Location: Remote or Hybrid work...Remote workFull timeWorldwide
$232k - $310k
...and high standards. Our engineers, product leaders, and go-to-... ...world works.About AII/ML TeamOur AI/ML team is... ...cutting-edge deep learning models across all Eightfold... ....Build robust, scalable, and reliable infrastructure... ...innovation through a blend of remote and in-person work. We...Remote workWork experience placementWork at officeFlexible hours3 days per week- ..., our proprietary models, and a sophisticated... ...’ Reasoning Engine and natural language... ...models and agents in production. We are an eval-... ...build on the latest ML/LLM research and... ...develop innovative, scalable and dynamic... ...personas (flexible, remote, or required in office...Remote workWork at officeImmediate startFlexible hours
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$250k - $400k
...built, trained, and run in production. This team is... ...The challenge isn't just model capability. It's building... .... It's building the engine that research runs on.... ...Experience building and scaling ML systems in production... ...(on-site or hybrid, remote considered case by case...Remote work- ...Senior Machine Learning Engineer Join Runware as a... ...and experimentation to production deployment and performance... ...source and third-party models into our inference... ...Infrastructure and Backend teams on scalable serving systems... ...and help raise the ML engineering bar across...Remote work
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