Member of Technical Staff in Machine Learning (AI)

Location: New York City, United States; full-time, on-site. Relocation support is available.

Base salary: $230,000–$350,000 per year, plus equity, depending on experience and scope of responsibility.

Company

hirify.global builds AI software that helps life sciences teams create, refine, and review pharmaceutical marketing content for leading life sciences manufacturers and pharma brands.

What you will do

• Turn product problems into clear ML objectives with useful baselines, relevant error costs, and explicit latency, cost, and reliability constraints.
• Investigate data and model failures through error analysis and targeted slices; improve label quality, dataset coverage, and handling of noisy or delayed reviewer feedback.
• Develop and compare retrieval, ranking, classification, representation, training, and fine-tuning approaches based on evidence and product constraints.
• Design controlled, reproducible experiments with appropriate data splits, leakage checks, uncertainty analysis, and generalization assessment.
• Connect offline improvements to customer outcomes in collaboration with Applied AI and product partners.
• Ship and operate model and data improvements through versioned releases, quality monitoring, rollback criteria, and reproducible documentation of results.

Requirements

• Strong ML fundamentals and hands-on implementation skills, including learning objectives, optimization, regularization, data quality, and generalization.
• Strong Python skills and experience with modern ML tools for implementing, inspecting, and improving model behavior.
• Evidence of taking a data or model improvement into production and understanding its post-deployment behavior.
• Sound experimental judgment, including explicit hypotheses, credible comparisons, meaningful baselines, leakage checks, noisy-label handling, and care with misleading aggregate metrics.
• Depth in at least one relevant area: retrieval and ranking, representation learning, NLP, model adaptation, or fine-tuning, with the ability to learn adjacent approaches.
• Practical software engineering skills for reproducible experiments, tested components, production integration, and debugging.
• Clear communication and personal ownership, including the ability to explain tradeoffs, collaborate with product and engineering partners, and follow through when results challenge assumptions.

Nice to have

• Experience with scientific documents, human review feedback, or regulated enterprise products.
• Healthcare or pharmaceutical experience.
• A particular degree, publication record, or framework is not required as a substitute for demonstrated implementation and experimental judgment.

Culture & Benefits

• Health, dental, and vision insurance.
• Ground-floor equity opportunity.
• Unlimited paid time off.
• 401(k) with a 4% company match.
• In-office lunches five days a week and a professional growth stipend.
• Visa sponsorship for O-1, H-1B, and TN visas, plus relocation support.