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AI/ML Software Engineer

Pay
Pay not listed
Work setting
Remote — work setting source
Listed location: Remote
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Employment
Not stated

What you’ll work on

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

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • 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
Qualification wording
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
Apply at ASG

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 30, 20265 days ago
Recorded sightings
4
Last seen by us
Nov 3, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 5

Early. Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

ASG is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add 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.

  • Python
  • R
  • SQL
  • BigQuery
  • Databricks
  • dbt
  • Hadoop
  • Iceberg
  • Kafka
  • Redshift
  • SageMaker
  • Spark
  • Airflow
Where the posting names them
- 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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About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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

  • Lead high-impact AI/ML and data engineering projects across ASG portfolio companies, partnering directly with operating companies to design, build, and deliver solutions
  • 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
  • Serve as a technical leader and trusted advisor to engineering and data teams across the portfolio, helping shape practical approaches to AI and data adoption
  • Contribute to enablement efforts across the portfolio by sharing practical guidance, examples, and best practices for AI/ML and data engineering
  • Support training sessions, workshops, and working sessions that help OpCo teams build stronger capabilities in AI, ML, and data infrastructure
  • Help establish repeatable patterns, playbooks, and best practices for building and deploying AI/ML and data solutions across multiple companies
  • Collaborate closely with portfolio leadership, product stakeholders, and engineering teams to identify where AI, ML, and better data infrastructure can drive measurable impact
  • Own the full delivery lifecycle from scoping through production handoff, including structured knowledge transfer that leaves teams capable of owning and extending what was built

Who You Are

  • 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
  • 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
  • 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
  • Knowledge of modern data architecture and best practices across ingestion, transformation, governance, quality, and access
  • Strong judgment around model performance, system reliability, security, and maintainability in production environments
  • Curiosity and discipline to stay current with the latest advancements in AI tooling, LLMs, and applied ML systems
  • Strong communication skills, with the ability to work effectively with engineering, product, data, and business stakeholders
  • Comfortable supporting cross-company enablement through knowledge sharing, collaboration, and practical guidance
  • Comfortable switching contexts quickly and operating effectively across multiple companies, teams, and priorities

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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