Harnham
Lead MLOps Engineer
Harnham - New York, New York, us, 10261
Work at Harnham
Overview
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Overview
Lead MLOps Engineer
$140,000-$160,000 + bonus + RSUs
Legal-tech
Remote
About the Organization
Join a global company delivering intelligent information and technology solutions to professionals in legal, tax, compliance, and corporate sectors. The team is part of the organization's innovation hub, focused on applying AI, ML, and data science to create forward-looking tools.
The environment combines the best of both worlds: startup energy with enterprise support. Projects include building agentic systems to automate tax prep and document summarization for legal and financial workflows.
About the Role
This is a model deployment-focused role-ideal for someone with a strong foundation in software engineering and a passion for making machine learning work in the real world. You'll lead experiments, iterate on PoCs, and help define how ML models are deployed, scaled, and maintained in production environments.
What You'll Bring 7+ years of software engineering experience in production environments 2+ years of experience working with ML systems (Python) Experience with ModelOps / MLOps workflows Background in: NLP: Named Entity Recognition / NER, information extraction, and information retrieval Numpy, Pandas, and scalable data handling Cloud environments (provider-agnostic) CI/CD pipelines, GitFlow, and Agile development Logging, alerting, testing, and autoscaling systems Strong collaboration and communication skills, including experience working with non-technical stakeholders Independent problem-solver with a proactive mindset Preferred Experience
Technical leadership on ML products Experience delivering LLM-based solutions Engineering management experience, including mentoring or leading cross-functional teams Familiarity with all stages of the AI product lifecycle Startup or fast-paced innovation environment experience
HOW TO APPLY
Please register your interest by sending your résumé to Cassie Wandell via the Apply link on this page.
KEYWORDS
Machine Learning | GenAI | Gen AI | Generative AI | LLMs | Large Language Models | Artificial Intelligence | MLOps | Production | Machine Learning Operations | AI | Artificial Intelligence | Containerization | PyTorch | Python | Deployment | Deploying | MLFlow | Kubernetes | Kubeflow | ModelOps | NLP | Natural Language Processing | GitFlow | NER | Information Extraction | Information Retrieval
About the Organization
Join a global company delivering intelligent information and technology solutions to professionals in legal, tax, compliance, and corporate sectors. The team is part of the organization's innovation hub, focused on applying AI, ML, and data science to create forward-looking tools.
The environment combines the best of both worlds: startup energy with enterprise support. Projects include building agentic systems to automate tax prep and document summarization for legal and financial workflows.
About the Role
This is a model deployment-focused role-ideal for someone with a strong foundation in software engineering and a passion for making machine learning work in the real world. You'll lead experiments, iterate on PoCs, and help define how ML models are deployed, scaled, and maintained in production environments.
What You'll Bring 7+ years of software engineering experience in production environments 2+ years of experience working with ML systems (Python) Experience with ModelOps / MLOps workflows Background in: NLP: Named Entity Recognition / NER, information extraction, and information retrieval Numpy, Pandas, and scalable data handling Cloud environments (provider-agnostic) CI/CD pipelines, GitFlow, and Agile development Logging, alerting, testing, and autoscaling systems Strong collaboration and communication skills, including experience working with non-technical stakeholders Independent problem-solver with a proactive mindset Preferred Experience
Technical leadership on ML products Experience delivering LLM-based solutions Engineering management experience, including mentoring or leading cross-functional teams Familiarity with all stages of the AI product lifecycle Startup or fast-paced innovation environment experience
HOW TO APPLY
Please register your interest by sending your résumé to Cassie Wandell via the Apply link on this page.
KEYWORDS
Machine Learning | GenAI | Gen AI | Generative AI | LLMs | Large Language Models | Artificial Intelligence | MLOps | Production | Machine Learning Operations | AI | Artificial Intelligence | Containerization | PyTorch | Python | Deployment | Deploying | MLFlow | Kubernetes | Kubeflow | ModelOps | NLP | Natural Language Processing | GitFlow | NER | Information Extraction | Information Retrieval