AI/ML Software Engineer

This is a fully remote position, open to applicants in California.

📋 Description

• Lead projects in AI/ML and data engineering for ASG portfolio companies.

• Collaborate with operating companies to design, construct, and implement solutions.

• Develop data pipelines, model integrations, internal LLM applications, APIs, and necessary infrastructure.

• Create LLM-driven tools and workflows to enhance business operations, boost productivity, and improve product functionalities.

• Identify avenues for monetizing data through products, features, and analytical offerings.

• Provide guidance to engineering and data teams on the adoption of AI and data practices.

• Share practical recommendations, case studies, and best practices related to AI/ML and data engineering.

• Facilitate training sessions, workshops, and collaborative working groups.

• Establish replicable patterns, playbooks, and best practices for AI/ML and data solutions.

• Work in conjunction with portfolio leadership, product stakeholders, and engineering teams.

• Oversee the entire delivery process from project scoping to production handoff, including knowledge transfer.

⛳️ Requirements

• Proven experience in implementing machine learning, data engineering, and applied AI solutions at scale.

• Knowledge of LLM-based applications, model APIs, retrieval workflows, evaluation strategies, and production deployment methodologies.

• Hands-on experience with various technologies such as Bedrock, SageMaker, Vertex AI, Glue, Airflow, Spark, Hadoop, Storm, time series databases, Parquet, Iceberg, Redshift, Kafka, Kinesis, BigQuery, Cassandra, OpenSearch/Elasticsearch, dbt, Monte Carlo, and Databricks.

• Proficient in developing solutions and analyzing data using Python, R, and SQL.

• Exceptional skills in data validation for LLM and ML solutions.

• Understanding of LLM fine-tuning and inference economics.

• Experience in crafting reliable forecasting solutions.

• Ability to translate business challenges and data opportunities into actionable AI/ML strategies.

• Familiarity with modern data architecture covering ingestion, transformation, governance, quality, and access.

• Strong judgment regarding model performance, system reliability, security, and maintainability in production environments.

• Capability to remain updated on AI tools, LLMs, and applied ML systems.

• Excellent communication skills with engineering, product, data, and business stakeholders.

• Comfortable supporting cross-company enablement through knowledge sharing and practical advice.

• Ability to adapt and operate across various companies, teams, and shifting priorities.

🏝️ Benefits

• Annual bonus.

• Employer-funded benefits.

• Learning and development stipend.

• Incentive pay for qualifying roles.

• Competitive total rewards package.