Machine Learning Engineer

Description

The company builds AI-powered features that turn large volumes of structured and unstructured data, such as reports, news and other text, into insights for users of its platform.

The Machine Learning Engineer works in the Product and Engineering group on the AI and ML Insights team, covering model design, training, deployment and upkeep, with focus areas in NLP, generative AI, LLMs and scalable data systems.

The team works with partners around the world, values constructive discussion and invests in learning through mentorship and training programs.

The field changes quickly and some work will be ambiguous, so the team expects people willing to take risks, learn from fast failures and try again.

If you are unsure you meet every requirement, you are still welcome to apply, as you may suit this role or another one at the company.

Responsibilities

• Build AI and ML capabilities that generate insight on the platform and support the team's strategic priorities.
• Design, build and deploy AI/ML models and services for NLP, summarization, semantic search, classification and prediction, meeting production reliability and efficiency standards.
• Build and tune classifiers, transformers, LLMs and other NLP methods to extract insight from structured and unstructured data, and integrate them into the wider AI/ML infrastructure with partner teams.
• Work with engineering, product management and data collection teams so models rest on high-quality data and serve product goals.
• Test new GenAI, NLP and search technologies, methods and tools, and turn promising findings into practical improvements.
• Help set standards for model transparency, monitoring, evaluation, compliance, security, data integrity and responsible AI use.
• Share knowledge through code and design reviews, pairing and documentation, guide junior engineers and help evaluate candidates and onboard new team members.
• Apply Agile, Lean and Fast-Flow practices to keep model development and release cycles efficient.
• Model the company's values and take on other company initiatives and projects as asked.

Requirements

• Bachelor's degree in Computer Science, Mathematics or Data Science.
• At least 2 years of software engineering or machine learning engineering experience, with a focus on AI/ML for insight generation, summarization, semantic search or prediction.
• You must be authorized to work in the United States, with no need for visa sponsorship now or later.
• Preferred: Hands-on experience with NLP and machine learning, including classifiers, transformer models, LLMs, and libraries such as scikit-learn, pandas, NumPy, TensorFlow and PyTorch.
• Preferred: Experience shipping production GenAI or LLM systems that had measurable business impact.
• Preferred: Familiarity with the LangChain ecosystem, including LangSmith and LangGraph, and production use of them is a strong plus.
• Preferred: Skill building and maintaining scalable data pipelines and distributed systems with tools such as Apache Kafka, Airflow and Snowflake.
• Preferred: Strong Python and SQL skills, with working knowledge of Java or Scala considered a plus.
• Preferred: Practical work with cloud-native development, containers and orchestration, such as Docker and Kubernetes.
• Preferred: Proven ability to solve hard technical problems, shape architecture and deliver fast, reliable solutions.
• Preferred: Clear communication and teamwork across product managers, engineers and data scientists in globally distributed teams.
• Preferred: Experience in fast-moving, data-driven settings. Exposure to fintech or financial data platforms is a strong advantage.
• Preferred: Authored papers at peer-reviewed AI/ML conferences such as NeurIPS, ICML or ACL and taken part in the wider AI research community is strongly preferred.

Conditions

Annual base salary is $125,000-$180,000.

Target annual bonus is 10%.

This role is in the office 5 days a week, since in-person work supports the collaboration and spontaneous exchange the team relies on across the company's global offices.

The work takes place in a standard office, using a PC and phone throughout the day.

Limited corporate travel may be required to visit remote offices or attend business meetings and events.

Benefits

• Comprehensive health coverage and extra medical wellness incentives.
• STD, LTD, AD&D and life insurance.
• Employee assistance program and Dependent Care FSA.
• Paid sabbatical after four years.
• Paid family and paternity leave.
• Generous vacation, sick and volunteer days.
• Annual education stipend, tuition reimbursement and CFA exam stipend.
• Robust training on industry and soft skills.
• Matching gifts program, employee resource groups, company-wide events, quarterly team building and a referral bonus.
• Subsidized emergency childcare.
• 401k match, shared ownership employee stock program and a monthly transportation stipend.
• Benefits and perks follow the relevant plan and policy documents and may change during employment.