Senior AI & Machine Learning Software Engineer

Growth Acceleration Partners • Colorado Springs, CO

9d

About The Position

Founded in 2007, Growth Acceleration Partners (GAP) is a consulting and technology services company. We consult, design, build and modernize revenue-generating software and data engineering solutions for clients. With modernization services and AI tools, we help businesses achieve a competitive advantage through technology. GAP’s remote, integrated engineering teams use end-to-end solutions to innovate and align with your business goals. We have 600+ English-speaking engineers based in Latin America and approximately 20 U.S.-based engineers. With some of the highest customer satisfaction scores in the industry, GAP’s focus is customer and employee success.
GAP is a woman-owned company headquartered in Austin Texas. We are a values-based company focused on growing our people by investing in education, onsite English classes and training in the latest technologies, including AI, data analytics and machine learning. Our goal is to provide solutions for our customers that help them achieve critical business outcomes, while enabling our GAPSters and our communities to attain long-term success.
Summary
We are looking for an AI / Machine Learning Software Engineer with hands-on experience across traditional Machine Learning and Generative AI / LLM-based systems. In this role, you will design, build, deploy, and operate production-grade AI solutions that combine data pipelines, ML models, and LLM workflows to deliver scalable, reliable, and measurable business impact.
This position is ideal for an engineer who enjoys taking AI systems from concept to production, balancing accuracy, performance, and cost, and collaborating closely with data, platform, and product teams. You will work on real-world ML and GenAI features, not experiments or proofs of concept.

Requirements

• 5 years of experience in Machine Learning, AI, or Software Engineering roles.
• Proven experience delivering ML and/or Generative AI solutions into production environments.
• Strong background working across data, modeling, and software integration layers.
• Strong understanding of ML fundamentals:
• Classification, regression, clustering
• Feature engineering and model evaluation
• Hands-on experience with ML frameworks such as Scikit-learn, PyTorch, or TensorFlow.
• Experience building and deploying ML models in production.
• Practical experience working with LLMs and Generative AI systems.
• Ability to design and implement:
• Prompting strategies
• RAG pipelines
• Tool-augmented or agent-based workflows
• Strong Python development skills.
• Solid SQL experience working with structured datasets.
• Experience integrating models via REST APIs and service-based architectures.

Nice To Haves

• Experience with RAG architectures, vector databases, and semantic search.
• Familiarity with LangChain, LlamaIndex, or similar LLM orchestration frameworks.
• Experience with embeddings and similarity-based retrieval.
• Exposure to LLM fine-tuning techniques (LoRA, PEFT, QLoRA).
• MLOps experience with tools such as MLflow, Kubeflow, Airflow.
• Experience with Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
• Background working with streaming or large-scale data systems (Kafka, Spark).
• Experience with time-series modeling, forecasting, or anomaly detection.

Responsibilities

• Build, deploy, and maintain production ML and Generative AI systems.
• Develop end-to-end ML pipelines, including:
• Data ingestion and preprocessing
• Feature engineering
• Model training, evaluation, and deployment
• Design and implement LLM workflows, including prompting strategies, RAG architectures, tools, and agent-based systems.
• Develop and maintain supervised and unsupervised ML models such as classification, regression, clustering, and anomaly detection.
• Perform feature engineering, hyperparameter tuning, and model validation.
• Integrate ML and LLM solutions into APIs and microservices.
• Monitor and improve model performance, drift, latency, accuracy, and cost in production.
• Collaborate with data engineers, platform teams, and product stakeholders to deliver scalable AI features.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level