Sage · 8 hours ago
Staff Machine Learning Engineer
Atlanta, GA
Full-time
Hybrid
Lead/StaffSage is a nimble team within Sage, building innovative services and solutions using generative AI and machine learning to turbocharge our users' productivity. The Staff Machine Learning Engineer will design and implement product features using AI and ML, develop internal ML platforms, and mentor other engineers in best practices.
Business Information SystemsEnterprise SoftwareHuman ResourcesInformation TechnologySoftware
Responsibilities
Design and implement product features and services that use AI and ML to augment and simplify our customers' workflows
Develop our internal ML platform to support our machine learning systems and our own efficiency
Monitor and optimize the quality and performance of our models, services, and tools
Collaborate with our AI Platform team to extend the capabilities of our machine learning platform
Design and write robust production-quality code to support our machine learning systems
Build and operate pipelines for accessing and enriching data for machine learning
Train, tune, and ship models
Mentor other ML engineers, software engineers, and data scientists in best practices
Work with product managers and data scientists to translate product/business problems into tractable machine learning solutions
Qualification
Required
Keen interest in artificial intelligence and machine learning and extensive practical experience with it
Expert knowledge and experience with relevant programming languages (incl. Python), frameworks (incl. Pycharm, OpenAI, HuggingFace, Spark, Azure, AWS)
Extensive experience with cloud environments (AWS, Azure, GCP)
Ability to write highly performant code working with big data
Bachelor's degree, preferably in a field that uses data science / machine learning techniques (e.g. computer science/engineering, statistics, applied math)
Fluency in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and predictive modelling
Proven quantitative and analytical skills with significant experience with data science tools
Ability to communicate complex ideas in machine learning to non-technical stakeholders
Preferred
Experience with one or more ML Ops frameworks — MLFlow, Kubeflow, Azure ML, Sagemaker
Demonstrated theoretical foundations in linear algebra, probability theory, or optimization
Experience and training in finance and operations domains
Deep experience with ML approaches: deep learning, generative AI, large language models, logistic regression, gradient descent
Experience wrangling complex and diverse data to solve real-world problems
Benefits
Competitive salaries
Comprehensive health, dental and vision coverage
401(k) retirement match (100% matching up to 4%)
32 days paid time off (21 personal days, 10 national holidays, 1 floating holiday)
18 weeks paid parental leave for birth, adoption or surrogacy offered 1 year after start date
5 days paid yearly to volunteer (through Sage Foundation)
$5,250 tuition reimbursement per calendar year starting 6 months after hire date
Sage Wellness Rewards Program ($600 wellness credit and $360 fitness reimbursement annually)
Library of on-demand career development options and ongoing training offerings
Company
Sage
At Sage, we knock down barriers with information, insights, and tools to help your business flow.
Founded in 1981
10001+ employees
H1B Sponsorship
Sage has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (8)
2024 (9)
2023 (3)
2022 (13)
2021 (6)
2020 (5)
Funding
Current Stage
Late StageLeadership Team
Alvaro Ramirez
CEO & President Southern Europe
Steve Hare
Chief Executive Officer
Recent News
2025-12-12
UK Investor Magazine
2025-12-09
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