Top Machine Learning Engineer Jobs in NYC
Design, implement, and scale critical machine learning components and services, build a next-generation training framework, optimize model performance, automate machine learning model lifecycle, collaborate across teams, and provide technical direction.
Looking for a Machine Learning Engineer with expertise in Python, Machine Learning, and Cloud Platforms to join the Optimization team at Beeswax, a part of FreeWheel. Responsibilities include working on computational challenges in user response prediction, bidding optimization, forecasting, and more. The role involves contributing to software engineering and machine learning projects, developing data pipelines, training and deploying machine learning models, and collaborating with teams to provide technical solutions.
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Seeking a Principal Machine Learning Engineer at Atlassian to drive the development and implementation of cutting-edge machine learning algorithms, collaborate with teams to integrate AI functionalities into products, and provide guidance to emerging ML engineers. Must have a Master's or PhD in a quantitative subject.
As a machine learning engineer, you will work on developing machine learning models and features for our content recommender system. You will collaborate with other teams, analyze customer behavior, and contribute to improving our solution.
Looking for a Machine Learning Engineer with expertise in Python, Machine Learning, and Data Science to join the Optimization team at Beeswax, a part of FreeWheel. Responsibilities include implementing and validating machine learning algorithms, developing data pipelines, training models, and collaborating with teams for technical solutions.
Machine Learning Engineer specializing in NLP to join the Responsible AI team at Grammarly. Develop and implement new ML solutions to improve safety and fairness of Grammarly products. Work in small cross-functional teams to leverage ML advances and human-centered design.
As an Applied Machine Learning engineer at Atlassian, you will work on developing cutting-edge machine learning algorithms, training models, and integrating AI functionalities into products. Responsibilities include designing system architectures, conducting model evaluations, and applying AI/ML to enhance Atlassian products.
Build, orchestrate, and monitor model pipelines, scale machine learning algorithms, implement ML Ops, write production-ready code, collaborate with client teams, and contribute to researching and evaluating new technologies.
Featured Jobs
Seeking a Machine Learning Architect to enhance Machine Learning and Artificial Intelligence R&D strategy to personalize the Qualtrics experience. Responsibilities include designing AI architectures, selecting appropriate AI technologies, guiding machine learning direction, collaborating with cross-functional teams, and optimizing ML systems for performance and scalability.
As a Machine Learning Engineer at Dropbox, you will design, build, evaluate, deploy and iterate on large scale ML systems, work with cross-functional teams to personalize users' experiences, and contribute to revolutionizing collaboration tools. Requires 2+ years of ML or AI system building experience and strong analytical skills.
Senior ML Engineer role at Grammarly's On-Device ML team, responsible for proposing, designing, and prototyping new features, building ML models, integrating models into user interfaces, launching and monitoring model deployment, and staying updated with academic research.
Snap Inc is looking for a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building robust products. The ideal candidate should have a strong understanding of machine learning approaches and algorithms, prioritize duties, and collaborate effectively.
Experiment with state-of-the-art algorithms to improve knowledge retrieval and search efficiency, develop NLP and Gen AI models for customer support, collaborate with cross-functional teams, monitor and evaluate model performance, and prepare reports on model trends.
As a Staff Machine Learning Engineer at Personio, you will be at the forefront of shaping their Machine Learning landscape. Your responsibilities will include providing technical leadership, collaborating with cross-functional teams, writing high-quality code, analyzing complex technical problems, and driving innovation and improvements. The role requires a Bachelor's degree in Computer Science or a related field, 10+ years of experience in software engineering with 5+ years of experience in Machine Learning, strong proficiency in Pytorch, Tensorflow, and NLP, and excellent problem-solving and communication skills.
Develop and implement machine learning models for fraud detection, analyze large datasets, collaborate with cross-functional teams, monitor model performance, and stay up-to-date with the latest machine learning and fraud detection techniques.
Develop and implement machine learning models for fraud detection, analyze datasets for fraudulent activities, collaborate with teams to mitigate fraud risks, monitor model performance, stay updated on machine learning trends, and prepare reports for stakeholders.
As a Senior Machine Learning Engineer in the Underwriting & Credit organization at Cash App, you will be responsible for designing, building, and managing distributed services and pipelines. You will lead impactful projects, ensure high code quality, collaborate with various teams, and contribute to the growth of development capabilities through mentoring.
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers. We want to redefine the world's relationship ...
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Seeking a Senior Staff Machine Learning Engineer to drive new initiatives in AI products at Taskrabbit. Responsibilities include developing advanced ML models, collaborating with cross-functional teams, and working on search platforms using NLP and graph analysis.
Build, optimize, and deploy machine learning models to support identity resolution and ads attribution. Collaborate with cross-functional teams to meet company objectives and stay up-to-date with the latest technology in machine learning.
As a Senior Machine Learning Engineer at Movable Ink, you will be responsible for developing core machine learning solutions and infrastructure, working on recommender system challenges, and collaborating with various engineering teams to advance the ML platform. The role offers the opportunity to work on cutting-edge technologies and make a significant impact on customer interactions.
The Senior Machine Learning Engineer (Modeling) - Underwriting and Credit at Cash App will build and integrate ML solutions for evaluating customer cash flow risk, support multiple products, optimize automated decisioning pipelines, experiment with modeling techniques, and partner cross-functionally with teams.
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Seeking a Senior Machine Learning Engineer to design and build ML models for classification, regression, and machine vision problems, perform hyper-parameter tuning, implement ML pipelines, and optimize prediction performance. The role requires a Bachelor's degree in computer science or a related field, 5+ years of dedicated experience, expertise in computer vision and NLP models using neural networks, and proficiency in ML frameworks like TensorFlow and PyTorch.
GoodRx is looking for an experienced Senior Machine Learning Engineer to enable and accelerate our machine learning efforts. The ideal candidate should possess practical, hands-on data and analytics technical expertise and strong understanding of various machine learning models. Responsibilities include developing and implementing analytical capabilities, building machine learning models and pipelines, improving infrastructure, and mentoring junior engineers.
Design, build, and productionize proprietary machine learning models to solve business challenges. Collaborate with product teams to frame machine learning problems and architect solutions. Stay updated on emerging tech and trends, conduct experiments, and share knowledge with the team. Mentor team members and lead agile development.
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