Senior Applied Machine Learning Engineer

Jobtailor; California (MO); On-site; USD 150,000 - 230,000; Full time

Job summary

Jobtailor is seeking a senior AI/ML engineer to design, develop, and deploy machine learning solutions addressing real-world customer problems. You will rapidly build demos and MVPs, integrating open-source tools like MLFlow, Spark, LangChain, Kubeflow, and Kubernetes into production.

The role emphasizes scalable models, collaboration with product teams, and mentoring junior staff. Ideal candidates hold a PhD or equivalent with extensive industry experience and strong Python/Go backend skills,

Qualifications

• PhD or equivalent with at least 2 years in industry.
• Hands-on ML/AI deployments in customer-facing environments.
• Production-ready ML models with reliable performance.
• Experience with open-source ML/AI tools and back-end languages (Python/Go).

Responsibilities

• Design, develop, and deploy ML models and AI solutions for real-world customer problems.
• Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities.
• Integrate open-source ML tools into production environments and platforms like Kubernetes.
• Fine-tune models for accuracy, efficiency, and scalability in production.
• Translate customer requirements into actionable AI/ML solutions and document procedures.
• Lead and mentor junior team members and communicate progress to leadership.

Skills

Python

Go

AI agents development

ML deployment

Communication skills

Education

PhD or higher / Master's with substantial experience

Tools

MLFlow

Spark

LangChain

Kubeflow

Kubernetes

Job description

Responsibilities

• Design, develop, and deploy machine learning models and AI solutions that address real‑world customer problems, focusing on usability, scalability, and performance.
• Rapidly develop demos, POCs, MVPs, and workflows to showcase new AI/ML capabilities that could be integrated into the product or used to improve existing features based on customer feedback or market research.
• Develop and improve integrations of open‑source ML/AI tools (MLFlow, Spark, LangChain, Kubeflow) within production environments, ensuring seamless operation on platforms like Kubernetes.
• Fine‑tune models and algorithms for accuracy, efficiency, and scalability in production settings, including deep‑learning technologies.
• Translate customer requirements and industry trends into actionable AI/ML solutions that improve product features, data management, and system performance.
• Work closely with product managers, data scientists, and engineering teams to brainstorm, design, and deploy AI/ML solutions, documenting procedures and best practices.
• Lead efforts in integrating emerging AI tools, mentor junior team members, and communicate progress and challenges to leadership.

Requirements

• PhD with at least 2 years of relevant industry experience, or the equivalent (Master’s degree with 4+ years, Bachelor’s with 6+ years).
• Extensive hands‑on experience applying machine learning and AI solutions in customer‑facing or end‑user environments.
• Proven ability to deploy models in production, ensuring reliability and performance.
• Experience with open‑source ML/AI tools and frameworks.
• Experience with backend programming languages (Python, Go).
• Proficiency in developing, using, and maintaining AI agents; proven experience coding agents for automation or decision‑making tasks.
• Excellent written and verbal communication skills, especially in asynchronous collaboration.

Core Competencies

Demonstrates expertise in designing and deploying machine learning models and AI solutions, with a strong focus on usability, scalability, and performance. Proficient in integrating open‑source ML/AI tools and collaborating with cross‑functional teams to translate customer needs into actionable solutions.

Tools & Technologies

• MLFlow
• Spark
• LangChain
• Kubeflow
• Kubernetes