Member of Technical Staff – AI / ML Platform Engineer

Alldus; New York (NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Salary: $210k

Equity

Job summary

Alldus in New York City is seeking a Senior AI / Machine Learning Platform Engineer to build and operate the ML infrastructure powering diagnostics and customer experiences across voice, chat and other agent workflows. You will own data processing, model development, deployment and continuous improvement, delivering scalable, production-ready AI features.

The role requires 5+ years in software or ML engineering, strong Python and TypeScript skills, and deep experience with distributed systems

Qualifications

• 5+ years of software or ML engineering experience delivering production systems.
• Strong coding in Python and TypeScript; production ML systems experience.
• Deep understanding of retrieval, indexing, evaluation and deployment in ML.

Responsibilities

• Develop and operate ML infrastructure for search, retrieval, indexing, training, evaluation, inference and deployment.
• Build models for diagnostics, fault prediction, ranking, information extraction and automation.
• Develop capabilities for voice and chat agents across channels; manage data pipelines.
• Maintain distributed services, data pipelines, and live inference with monitoring and capacity planning.
• Design evaluation frameworks linking model accuracy to customer outcomes.
• Improve models from conversation data and human feedback.
• Strengthen engineering workflows with automated testing, CI/CD, observability and reusable infra.
• Collaborate with product engineers and domain experts to productionize AI features.
• Make architecture decisions around internal vs third-party solutions and open-source tools.

Skills

Python

TypeScript

ML infra

Distributed systems

CI/CD

Cloud platforms

Model deployment

Tools

GPUs

CI/CD pipelines

Experiment tracking

Job description

Our client, an early-stage AI Software company, is hiring a Senior AI /Machine Learning Platform Engineer to join their team in New York City. The successful candidate will develop the models and infrastructure powering diagnostics and customer experience, building shared AI capabilities across voice, chat and other agent workflows while taking ownership from data processing and model development through to deployment and continuous improvement.

Responsibilities

• Develop and operate machine learning infrastructure supporting search, retrieval, indexing, training, evaluation, inference and model deployment.
• Build and refine models for diagnostics, fault prediction, parts selection, ranking, information extraction and customer-support automation.
• Develop shared capabilities for voice and chat agents, covering context, memory, knowledge retrieval, tools, policies and continuity across channels.
• Create data and feedback pipelines drawing on service histories, technical documentation, equipment data, conversations, images and repair results.
• Maintain reliable distributed services, data pipelines, search systems and live inference through performance monitoring, capacity planning and failure recovery.
• Design evaluation frameworks that link model accuracy and retrieval quality to customer experience and repair outcomes.
• Turn conversation data, agent activity and human feedback into ongoing improvements to models and agent performance.
• Strengthen engineering workflows through automated testing, CI/CD, observability, reusable infrastructure and controls for AI-generated code.
• Collaborate with product engineers and domain experts to bring fast, explainable and dependable AI features into production.
• Make practical architecture decisions around internal development, third-party solutions, compute, storage, model providers and open-source tools.

Skillset

• At least 5 years' professional experience in software or machine learning engineering, including delivery of production systems.
• Strong coding skills in Python and TypeScript, with confidence working across models, backend systems, data platforms and cloud infrastructure.
• Sound knowledge of modern search and ML systems, including retrieval, indexing, evaluation, deployment and the challenges of models running in production.
• A strong understanding of distributed systems, performance tuning, reliability, observability and infrastructure costs.
• Experience applying AI development tools to increase productivity while maintaining engineering standards.
• The flexibility to move between research, infrastructure and product development as priorities evolve.
• An interest in creating reusable AI capabilities across diagnostics, customer support and multiple communication channels.
• A proactive approach, strong ownership and a focus on delivering measurable value to customers.
• Experience with ranking, recommendation engines, vector or graph search, multimodal models or real-time inference is desirable.
• Familiarity with ML platforms, evaluation frameworks, developer tools, GPUs, inference optimization, infrastructure as code or incident response would be an advantage.

Benefits

• Salary: $210k.
• Equity.