Machine Learning Engineer (Remote Eligible) 3+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc 3+ years of experience in developing deep learning (especially NLP models) and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc 4+ years of programming experience in languages used in AI/ML (eg python, scala etc) Strong applied data science skills – ability to recognize data patterns, understand how and when to use various machine learning approaches (eg supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg Experience developing, documenting, and supporting REST APIs A degree in Computer Science, Engineering, or a related field or equivalent practical experience Legally eligible to work in the U.S. on an ongoing basis Responsibilities Build and deploy Machine Learning (ML) models and data pipelines, from training to inference, in production using MLOps best practices Use pre-trained Generative AI models, deep learning models or traditional machine learning models to solve customer problems Monitor and maintain production ML models by identifying and correcting for model drift/staleness, incorporating user feedback loops, and retraining models as necessary Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom built models Distill complex ML concepts into easy to follow technical documentation Partner effectively with software engineers and product managers to integrate the machine learning solution into the product HSA, 100% employer-paid premiums, or buy-up medical/vision and dental coverage options for full-time employees Equity – Restricted Stock Units (RSUs) for eligible roles Lucrative Employee Stock Purchase Program (15% discount) 401k Match to help you save for your future (50% of your contribution up to the first 6% of your eligible pay) Monthly stipend to support your work and productivity US employees are automatically covered under Smartsheet-sponsored life insurance, short-term, and long-term disability plans US employees receive 12 paid holidays per year Up to 24 weeks of Parental Leave Personal paid Volunteer Day to support our community Opportunities for professional growth and development including access to LinkedIn Learning online courses Company Funded Perks, including a counseling membership, local retail discounts, and your own personal Smartsheet account Actual compensation is determined by several factors including, but not limited to, level of professional, educational experience, skills, and specific candidate location Qualifications 3+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc 3+ years of experience in developing deep learning (especially NLP models) and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc 4+ years of programming experience in languages used in AI/ML (eg python, scala etc) Strong applied data science skills – ability to recognize data patterns, understand how and when to use various machine learning approaches (eg supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg Experience developing, documenting, and supporting REST APIs A degree in Computer Science, Engineering, or a related field or equivalent practical experience Legally eligible to work in the U.S. on an ongoing basis Responsibilities Build and deploy Machine Learning (ML) models and data pipelines, from training to inference, in production using MLOps best practices Use pre-trained Generative AI models, deep learning models or traditional machine learning models to solve customer problems Monitor and maintain production ML models by identifying and correcting for model drift/staleness, incorporating user feedback loops, and retraining models as necessary Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom built models Distill complex ML concepts into easy to follow technical documentation Partner effectively with software engineers and product managers to integrate the machine learning solution into the product Benefits HSA, 100% employer-paid premiums, or buy-up medical/vision and dental coverage options for full-time employees Equity – Restricted Stock Units (RSUs) for eligible roles Lucrative Employee Stock Purchase Program (15% discount) 401k Match to help you save for your future (50% of your contribution up to the first 6% of your eligible pay) Monthly stipend to support your work and productivity Flexible Time Away Program, plus Incidental Sick Leave US employees are automatically covered under Smartsheet-sponsored life insurance, short-term, and long-term disability plans US employees receive 12 paid holidays per year Up to 24 weeks of Parental Leave Personal paid Volunteer Day to support our community Opportunities for professional growth and development including access to LinkedIn Learning online courses Company Funded Perks, including a counseling membership, local retail discounts, and your own personal Smartsheet account Actual compensation is determined by several factors including, but not limited to, level of professional, educational experience, skills, and specific candidate location In 2005, Smartsheet was founded on the idea that teams and millions of people worldwide deserve a better way to deliver their very best work. Today, we deliver a leading cloud-based platform for work execution, empowering organizations to plan, capture, track, automate, and report on work at scale, resulting in more efficient processes and better business outcomes. You will report to our Sr… Director, Data Science & BI located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. You Will: Build and deploy Machine Learning (ML) models and data pipelines, from training to inference, in production using MLOps best practices. Use pre-trained Generative AI models, deep learning models or traditional machine learning models to solve customer problems. Monitor and maintain production ML models by identifying and correcting for model drift/staleness, incorporating user feedback loops, and retraining models as necessary. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom built models. Distill complex ML concepts into easy to follow technical documentation. Partner effectively with software engineers and product managers to integrate the machine learning solution into the product. You Have: 3+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. 3+ years of experience in developing deep learning (especially NLP models) and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc. 4+ years of programming experience in languages used in AI/ML (eg python, scala etc) Strong applied data science skills – ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs). Experience developing, documenting, and supporting REST APIs A degree in Computer Science, Engineering, or a related field or equivalent practical experience. Legally eligible to work in the U.S. on an ongoing basis Perks & Benefits: HSA, 100% employer-paid premiums, or buy-up medical/vision and dental coverage options for full-time employees Equity – Restricted Stock Units (RSUs) for eligible roles Lucrative Employee Stock Purchase Program (15% discount) 401k Match to help you save for your future (50% of your contribution up to the first 6% of your eligible pay) Monthly stipend to support your work and productivity Flexible Time Away Program, plus Incidental Sick Leave US employees are automatically covered under Smartsheet-sponsored life insurance, short-term, and long-term disability plans US employees receive 12 paid holidays per year Up to 24 weeks of Parental Leave Personal paid Volunteer Day to support our community Opportunities for professional growth and development including access to LinkedIn Learning online courses Company Funded Perks, including a counseling membership, local retail discounts, and your own personal Smartsheet account Teleworking options from any registered location in the U.S. (role specific) Smartsheet provides a competitive base salary range for roles that may be hired in different geographic areas we are licensed to operate our business from. Actual compensation is determined by several factors including, but not limited to, level of professional, educational experience, skills, and specific candidate location. In addition, this role will be eligible for a market Company information Smartsheet (NYSE: SMAR) is the enterprise platform for modern work management. By aligning people and technology so organizations can move faster and drive innovation, Smartsheet enables its millions of users to achieve more. Visit to learn more.Backed by enterprise-grade security, Smartsheet is used by more than 75% of the companies in the Fortune 500 to implement, manage, and automate processes across a broad array of departments and use cases. Software, Information Technology, Enterprise Software, Financial Services, Technology, Cloud Computing, Data Analysis, Computer Software, Internet, Information Technology and Services Company Specialties: productivity, collaboration, achievement, innovation, effectiveness, security, work management, reporting, automation, scale, collaborative work management, and project management #J-18808-Ljbffr
scikit-learn Artificial intelligence (AI) Amazon Web Services (AWS) Computer Science Enterprise architecture (EA) automation Azure Writing reports and proposals cloud-computing MLOps Google Cloud Platform (GCP) deep-learning Security Docker Information technology (IT) Machine Learning supervised-learning Engineering aws-glue Amazon SageMaker Project management Finance Business Intelligence (BI) scale OpenAI LangChain Innovativeness Natural language processing (NLP) GenAI REST Data Analyst Scala Lambdas Python Data Science Hugging Face Internet unsupervised-learning Collaboration TensorFlow PyTorch