Senior AI & Machine Learning Software Engineer at Growth Acceleration Partners

Position Senior AI & Machine Learning Software Engineer
Posted 03 Mar 2026
Expired 02 Apr 2026
Company Growth Acceleration Partners
Location United States | US
Job Type Full Time

Job Description:

Latest job information from Growth Acceleration Partners for the position of Senior AI & Machine Learning Software Engineer. If the Senior AI & Machine Learning Software Engineer vacancy in United States matches your qualifications, please submit your latest application or CV directly through the updated Jobkos job portal.

Please note that applying for a job may not always be easy, as new candidates must meet certain qualifications and requirements set by the company. We hope the career opportunity at Growth Acceleration Partners for the position of Senior AI & Machine Learning Software Engineer below matches your qualifications.

WHAT WE DO

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 a Senior AI / Machine Learning Software Engineer with strong experience building and shipping production-grade ML and Generative AI systems.

This role goes beyond experimentation — we are seeking an engineer who has successfully deployed ML and LLM-powered features into real-world environments. You will design, build, and maintain scalable AI systems that leverage embeddings, semantic search, fine-tuned models, and distributed data pipelines across modern cloud platforms.

The ideal candidate combines deep ML knowledge with strong engineering fundamentals, production deployment experience, and a practical understanding of MLOps and containerized infrastructure.

Education
  • Bachelor’s or Master’s Degree in Computer Science, Data Science, Engineering, or related field, or equivalent practical experience.
Professional Experience
  • 5+ years of experience in Machine Learning or AI Engineering
  • Proven experience shipping ML + Generative AI systems into production
  • Strong Python engineering background
  • Experience deploying models in cloud environments (AWS, Azure, or GCP)
Key ResponsibilitiesMachine Learning & Model Development
  • Design, train, and deploy ML models (classification, regression, clustering, anomaly detection)
  • Build and optimize feature engineering pipelines
  • Evaluate models using appropriate metrics and validation techniques
  • Monitor model drift, performance degradation, and system reliability
Generative AI & LLM Systems
  • Design and operate LLM workflows (prompt engineering, RAG, tool usage, agents)
  • Implement embedding-based retrieval and semantic search systems
  • Develop and deploy fine-tuned models (LoRA, PEFT, QLoRA)
  • Optimize LLM systems for latency, accuracy, and cost efficiency
  • Evaluate hallucination risk and implement mitigation strategies
Production & MLOps
  • Build end-to-end ML pipelines (data ingestion → training → deployment → monitoring)
  • Use MLOps tools such as MLflow, Kubeflow, or Airflow
  • Containerize ML services using Docker
  • Deploy and manage ML workloads using Kubernetes
  • Integrate models into REST APIs and microservices
  • Implement CI/CD practices for ML systems
Large-Scale & Distributed Systems
  • Work with streaming or large-scale data systems (Kafka, Spark)
  • Design scalable AI pipelines capable of handling high-volume data
  • Collaborate with platform and infrastructure teams
Required Technical Skills
  • Strong Python development experience
  • Deep understanding of ML fundamentals
  • Hands-on experience with embeddings and semantic search
  • Experience fine-tuning LLMs (LoRA, PEFT, QLoRA)
  • Experience deploying ML models to production environments
  • Practical experience with MLOps tools (MLflow, Kubeflow, Airflow)
  • Docker and Kubernetes experience
  • Strong SQL and structured data experience
  • Familiarity with REST APIs and service-based architectures
Nice to Have
  • Experience with LangChain, LlamaIndex, or similar frameworks
  • Experience with vector databases
  • Exposure to large-scale distributed systems
  • Experience optimizing AI workloads for cloud cost efficiency
Soft Skills
  • Advanced English proficiency
  • Strong systems-thinking mindset
  • Ability to evaluate tradeoffs (accuracy vs latency vs cost)
  • Ownership mentality and delivery focus
  • Comfortable collaborating across data, platform, and product teams

At Growth Acceleration Partners, we're an equal opportunity employer committed to building a diverse and inclusive team. We value everyone's unique background, and we provide equal opportunities regardless of race, color, creed, religion, sexual orientation, gender identity, age, national origin, disability, marital status, veteran status or any other personal right protected by law. We foster a culture of belonging and strive to provide a welcoming environment where everyone feels safe to contribute and grow.

Job Info:

  • Company: Growth Acceleration Partners
  • Position: Senior AI & Machine Learning Software Engineer
  • Work Location: United States
  • Country: US

How to Submit an Application:

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