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Day 5
Early. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Listed location: RemoteRead the full posting
Lead AI/ML and data engineering projects, from scoping through production handoff
Build data pipelines, model integrations, APIs, and internal LLM applications
Develop LLM-powered tools and workflows for operations and products
Find ways to commercialize data through new products, features, and analytics
Run training, workshops, and knowledge transfer so teams can own what was built
Lead high-impact AI/ML and data engineering projects across ASG portfolio companies
Build hands-on across AI/ML systems, including data pipelines, model integrations, internal LLM applications, APIs, and supporting infrastructure
Develop LLM-powered tools and workflows that enhance business operations, internal productivity, and product capabilities
Partner with portfolio companies to identify opportunities to commercialize data through new products, features, and analytics offerings
Support training sessions, workshops, and working sessions that help OpCo teams build stronger capabilities in AI, ML, and data infrastructure
Demonstrated experience in deploying machine learning, data engineering, and applied AI solutions to solve customer and business challenges at scale
Familiarity with LLM-based applications, model APIs, retrieval workflows, evaluation approaches, and production deployment patterns
Experience developing solutions and analyzing data in Python, R and SQL
Understanding of fine tuning an LLM and strong understanding of inference economics and good judgment about when it’s better to use a frontier model or fine tune a smaller or open source model
Experience with developing solutions to reliably perform forecasting of various metrics (such as: sales projections, budget forecasts, resource consumption, demand forecasting, capacity planning, etc)
Experience translating business problems and data opportunities into practical AI/ML solutions
Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 5
Early. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Have developed production solutions with several (but certainly not all) of the following technologies: Bedrock, Sagemaker, Vertex AI, Glue, Airflow, Spark, Hadoop, Storm, time series databases, Parquet, Iceberg, Redshift, Kafka, Kinesis, Big Query, Cassandra, Open/Elastic Search, dbt, Monte Carlo and Databricks - Experience developing solutions and analyzing data in Python, R and SQL - Excellence in data validation — ensuring solutions developed with LLM and ML technologies produce results that are valid and grounded in reality
- Familiarity with LLM-based applications, model APIs, retrieval workflows, evaluation approaches, and production deployment patterns - Have developed production solutions with several (but certainly not all) of the following technologies: Bedrock, Sagemaker, Vertex AI, Glue, Airflow, Spark, Hadoop, Storm, time series databases, Parquet, Iceberg, Redshift, Kafka, Kinesis, Big Query, Cassandra, Open/Elastic Search, dbt, Monte Carlo and Databricks - Experience developing solutions and analyzing data in Python, R and SQL
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Company Description
ASG is an unconventional group of market-leading SaaS software companies, serving industries ranging from behavioral health to transportation to childcare. ASG believes deeply in the power of people and data to grow great organizations, and that sharing knowledge, expertise, and resources across its community of businesses drives exponential growth. ASG has acquired over 50 businesses since its inception in August of 2016. We are backed by Alpine Investors and operated by world-class PeopleFirstTM leaders. Founders of leading SaaS companies continue to trust ASG to grow their businesses and build even stronger legacies for the future. To learn more, visit www.alpinesg.com.
We hire and unleash a diverse array of leaders across ASG whose will to win - and ability to do so with love - is the true magic behind our success.
Job Description
This role is a hands-on builder for ASG’s portfolio companies, focused on developing AI/ML systems and data platforms that unlock new value from data. The AI/ML Engineer will lead and contribute directly to projects such as internal LLM applications, data pipelines, ML-powered product capabilities, and scalable data infrastructure. This person will work closely with operating companies to turn data into practical business outcomes, whether by enabling new products, improving decision-making, or building the technical foundations for AI adoption.
What You Will Do
Who You Are
Base Salary Range
The target salary range for this position is ($200,000 – $250,000), and is part of a competitive total rewards package including an annual bonus, employer-paid benefits, L&D stipend and incentive pay for eligible roles. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually at minimum to ensure competitive and fair pay.
A Secure Candidate Experience
All official emails and messages regarding opportunities at ASG, LLC, will come from our alpinesg.com email domain. Please be wary of communications from similar domains that may contain misspellings or slight variations. These could be attempts at phishing or impersonation. ASG will never ask you for sensitive personal information during the hiring process such as social security numbers, banking information or other personal details.
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Remote
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