This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re looking for a hands-on, results driven Machine Learning Engineer (Applied Machine Learning) to join our AdTech Optimization team. This is an Applied Machine Learning role focused on impact. You’ll work on data heavy Machine Learning projects that use large multi-table datasets to build and iterate on predictive models that influence the core of our Ad business. This role is focused on Model training using proven libraries and maintaining model health through retraining and continuous improvement. You will work in a Machine Learning focused team that delivers multiple area reliable Machine Learning projects. - Model Implementation: Train and evaluate ML/AI models using proven libraries, focus on delivery in short cycles of improvement. - Data analysis and feature engineering: Analyze large scale AdTech datasets across multiple sources and tables to understand patterns and opportunity areas. - End to end execution: Build and maintain data processing pipelines that generate features consistently and reproducibly. - Model evolution: Retrain and improve existing models by introducing new models and suggesting new features, adapting to shifting market dynamics. - Collaborate with other Engineering teams and PM: Communicate tradeoffs, explain model behavior and align on milestones and rollout plans. - Impact first: Contribute production quality code: tests, reviews, documentation and best practices. Qualifications - Bachelor’s degree in Computer Science, Computer Engineering. - 3+ years of industry experience in ML engineering / Data Science / Applied ML (or equivalent) with AI/ML model training. - Strong coding skills in Python and SQL, experience building ML/AI models for optimization / prediction problems using standard libraries. - Ability to analyze big data and make decisions on Model feature inputs and experience working with online feature stores. - Comfortable working with large datasets and multi-table joins. - Solid understanding in feature engineering and how feature choices affect model performance. - Ability to execute with some guidance, strong critical thinking and clear communication. Benefits - Medical (100% paid option), dental (100% paid), vision (100% paid). - Unlimited PTO/Vacation. - Life insurance (100% paid). - 401K with competitive contribution. - Annual, all-inclusive company trip for you and a guest. Previous destinations include Hawaii, a Mexican Riviera Cruise, Las Vegas and Los Cabos! - In the office we offer things like free lunch, free snacks, and free drinks. - Casual workplace that includes a relaxed dress code, plus a newly remodeled office in the heart of Irvine. - Growth, growth, growth - we are growing, and we would love for you to join us on the ride. - Annual Game Jam to show off your creative chops! Company Description MobilityWare is one of the leading mobile game publishers of card and puzzle games. With our headquarters in the heart of Orange County and a growing studio in Utah, we’re dedicated to our mission of bringing joy to others one game at a time. Ever since our flagship title Solitaire hit the Apple App Store on the day it opened in 2008, MobilityWare has been entertaining gamers around the world. With a product portfolio that includes beloved hits such as FreeCell, MONOPOLY Solitaire, Spades, Hearts, Mahjong, and Bubble Shooter Pop, our games have been downloaded over 600 MILLION times. MobilityWare was recently named one of Built in LA’s Best Places to Work for the fifth year in a row and we’ve been recognized as one of the Best Places to Work in Orange County five times by the Orange County Business Journal and OC Register. While we’re proud to be the company behind some of mobile gaming’s most popular titles, our most important achievement is creating a work environment that encourages professional growth and prioritizes the wellness of all of our team members.

• Design, implement, and optimize FPGA logic using AMD/Xilinx toolchains (Vivado, Vitis, HLS) development in VHDL/Verilog • Integrate FPGA designs into larger systems, ensuring robust verification, documentation, and deployment across multiple platforms (Zynq, UltraScale+, Versal) • Develop innovative machine learning and computer vision solutions to analyze and exploit large, complex datasets from remote sensing phenomenology • Develop algorithms and associated software tools using C/C++/Python and associated machine learning libraries (PyTorch, LibTorch) • Train AI/ML models and tune their hyperparameters for a given dataset and algorithm objectives • Provide solutions for data collection and data linting that enable rapid, automated curation of training data • Keep up with the SoTA practices for AI/ML • Adhere to teams’ standards for reviewing source code, unit-testing, source code control, and documentation practices • Utilize Python PEP8 standards.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Machine Learning Engineer at Artera, you’ll work on the AI Platform team with a focus on establishing scalable and efficient pipelines for data processing and model training. You’ll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You’ll ensure that Artera’s model developers can rely on highly efficient, large-scale training regimes and deploy optimized models to production environments. - Develop the long term vision and roadmap for Artera’s AI platform that will allow the company to continue to scale in terms of both increased inference volume and development workloads. - Accountable for Artera’s ML compute infrastructure including scaling up Artera’s Foundation Model development by developing distributed training infrastructure and developer libraries. - Build and evolve the core libraries used by AI scientists to develop, launch, and monitor AI products. - Work with model developers to optimize GPU and CPU efficiency and data throughput of large-scale foundation models and downstream model training runs. - Optimize Artera’s ability to store and serve terabytes of digital pathology data efficiently for the use in serving large-scale training regimes. - Ensure that Artera’s observability infrastructure provides a clear picture of how to continue to optimize performance across our model landscape. Qualifications - 8+ years of industry software engineering experience - 4+ years of industry experience in using ML orchestration frameworks such as Flyte, Ray, Kubeflow, Metaflow, MLFlow, Dagster, Argo Workflow or Prefect - 4+ years of industry experience using one of PyTorch, TensorFlow, or JAX in Python - 3+ years of industry experience building with AWS, Docker, and Kubernetes - 1+ years of industry experience optimizing large-scale, high data-throughput, distributed machine learning training pipelines Requirements - Experience using Terraform, SqlAlchemy - Experience in multi-node and multi-gpu training. - Experience deploying and maintaining infrastructure for machine learning training and production inference - Familiarity with TorchScript, ONNXRuntime, DeepSpeed, AWS Neuron or similar approaches to inference optimization Benefits - $180,000 - $220,000 a year - Equity is a core component of our compensation. - 401k matching - Unlimited paid time off (PTO) - The base salary is competitive and commensurate with experience, qualifications, and other factors to be discussed during the interview process. Work Authorization Requirement This is a remote role open to candidates who are currently authorized to work either in the United States or in Canada without the need for current or future employment-based visa sponsorship. Artera does not sponsor visas for this position. - Individuals authorized to work in the United States on a permanent basis (e.g., U.S. citizens, U.S. permanent residents), or - Individuals authorized to work in Canada (e.g., Canadian citizens or Canadian permanent residents). - Visa Transfers (if needed). Equal Employee Opportunity At Artera, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients and physicians. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are looking for a Principal Machine Learning Engineer, a senior technical visionary, to be the Principal Technical Lead for the Growth Engineering team, responsible for setting up overall technical strategy, unified technical architecture and defining a roadmap for industry leading methodology for user and engagement growth. Strong hands-on machine learning background including deep learning architectures, generative AI, and large scale deployment and measurement of ML systems is required. As the Principal Machine Learning Engineer you'll be responsible for the technical direction, strategy and health of our Growth Engineering org. You'll ensure that our technology can deliver on the business/product requirements necessary to keep Pinterest as an engaging platform for everyone. This means working with other leads to set and execute a long-term strategy for the overall engagement growth of Pinterest, aligning the strategy with other internal partners where it makes sense and communicating to leadership our current status and path to having world-class Growth capabilities. You'll also foster a healthy community where all ML engineers can learn best practices, collaborate effectively and understand our technical direction. What you’ll do: - Develop strong partnerships with product teams to understand and proactively address future technology needs and current developer pain points. - Champion and drive large-scale, cross-functional initiatives that grow user visitation and engagement depth of our platform. - Act as the ultimate "advocate" for engineers on Growth including representing needs to leadership and prioritizing projects on the platform teams that ensure high quality capabilities and a world-class Pinner experience. - Scale your leadership through both direct mentorship and via best practices, processes, training and tools. - Ensure solid technical plans are in place for projects within Growth via direct review or delegation. - Be the technical point of contact for decisions that impact the whole Pinterest platform via the Growth initiatives and for cross-functional partners for an 125+ member org. Qualifications - Deep expertise building large scale ML systems at scale with modern frameworks. - Knowledge of (and a passion for) building responsible and quality first discovery surfaces to drive user visitations. - Track record of innovating and delivering large, cross-functional projects across multiple organizations. - Strong written and verbal communication skills and proven ability to collaborate cross-functionally. - Degree in Computer Science, Machine Learning, Statistics or related field. - 10+ years of professional experience as a hands-on engineer and technical leader leading multiple projects. Requirements - This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country. - This position is not eligible for relocation assistance. Benefits - Visit our PinFlex page to learn more about our working model.