AI Engineer - Build Production-Ready ML Solutions

Jobtailor; Massachusetts; On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor is seeking an experienced AI/ML engineer in Massachusetts to design, build, and deploy end-to-end AI/ML solutions using LLMs, deep learning, and probabilistic modeling. You will independently frame problems, define success metrics, and drive evaluation criteria in collaboration with stakeholders.

The role emphasizes rapid prototyping, rigorous performance evaluation, and production-grade deployment with a focus on responsible AI and scalable cloud infrastructure.

Qualifications

• 4+ years of experience in data science, machine learning, or AI engineering.
• 4+ years across ML, statistics, NLP, and LLMs including generative AI and evaluation of LLM performance across foundation models.
• Experience building and deploying production AI systems with model integration, API development, and cloud-based infrastructure.
• Proficiency in Python with clean, tested, production-quality code.
• Bachelor’s degree in CS, statistics, applied mathematics, EE, physics, or related field.

Responsibilities

• Design, build, and deliver end-to-end AI/ML solutions for defined business use cases using LLMs, deep learning, agentic AI, and probabilistic modeling.
• Frame and scope AI problems independently, define success metrics and evaluation criteria with stakeholders.
• Design and conduct rigorous evaluations of AI system performance, including experiments and benchmarking across models.
• Build rapid prototypes to test AI approaches and advance validated solutions into production-grade applications.
• Apply best practices in AI development, responsible AI deployment, and production engineering.

Skills

Data science

Machine learning

AI engineering

Python programming

Prompt engineering

Education

Bachelor's degree (CS / Math / Stats / related)

Tools

Cloud infrastructure

API development

Production-grade coding

Job description

Jobtailor is seeking an experienced AI/ML engineer in Massachusetts to design, build, and deploy end-to-end AI/ML solutions using LLMs, deep learning, and probabilistic modeling. You will independently frame problems, define success metrics, and drive evaluation criteria in collaboration with stakeholders.

The role emphasizes rapid prototyping, rigorous performance evaluation, and production-grade deployment with a focus on responsible AI and scalable cloud infrastructure.