> Markdown version of [/jobs/ext/4483056-ai-ml-software-engineer](https://www.wearedevelopers.com/jobs/ext/4483056-ai-ml-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI/ML Software Engineer

- **Company:** ALPINE
- **Location:** United States (Remote available)
- **Salary:** $200,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Data Analysis, BigQuery, Data Architecture, Data Validation, Information Engineering, Data Infrastructure, Data Systems, Elasticsearch, R (Programming Language), Apache Hadoop, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Standard Sql, Software Deployment, Parquet, Time Series Databases, Large Language Models, Apache Spark, Model Validation, Reliability of Systems, Generative AI, Cassandra, Apache Kafka, Data Management, Machine Learning Operations, Data Pipelines, Amazon Redshift, Databricks
- **Published:** October 31, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6687b4849c7758f5

## About the Role

* 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

## 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