Sr. Machine Learning Engineer
PitchBook Data1 day ago
Base Salary
$170k - $240k/yr
Responsibilities
- Design, build, deploy, optimize, and maintain production AI and machine learning models and services.
- Develop NLP capabilities for summarization, semantic search, classification, prediction, and insight generation.
- Build models using classifiers, transformer models, LLMs, and other NLP techniques, integrating them into AI/ML infrastructure.
- Develop scalable, high-performance systems and data solutions that meet production reliability and efficiency standards.
- Collaborate with engineering, product management, data science, and data collection teams to align models with product and business goals.
- Contribute to architecture decisions and best practices for model transparency, monitoring, evaluation, compliance, security, data integrity, and responsible AI.
- Research emerging GenAI, NLP, and search technologies and translate findings into practical solutions.
- Mentor peers, participate in code and design reviews, evaluate candidates, and support onboarding and knowledge sharing.
Requirements
- Bachelor’s degree in Computer Science, Mathematics, or Data Science.
- 6+ years of experience in software engineering or machine learning engineering focused on AI/ML applications.
- Hands-on expertise with NLP, classifiers, transformer models, LLMs, and ML/data science libraries.
- Experience delivering production-grade GenAI or LLM-based systems with measurable business impact.
- Experience building scalable data pipelines and distributed systems with technologies such as Apache Kafka, Airflow, and Snowflake.
- Strong Python and SQL skills; Java or Scala experience is a plus.
- Experience with Docker, Kubernetes, and cloud-native development.
- Ability to solve complex technical problems, contribute to architecture, and deliver reliable, high-performance solutions.
- Experience collaborating cross-functionally in globally distributed, data-driven environments.
- Fintech or financial data platform experience is advantageous.
- Research papers at peer-reviewed AI/ML conferences such as NeurIPS, ICML, or ACL and participation in the AI research community are strongly preferred.
- Must be authorized to work in the United States without current or future visa sponsorship.
Benefits
- Comprehensive health benefits, medical wellness incentives, STD, LTD, AD&D, and life insurance.
- Paid sabbatical after four years, paid family and paternity leave, educational stipend, tuition reimbursement eligibility, CFA exam stipend, training programs, employee assistance program, and vacation, sick, and volunteer days.
- Matching gifts, employee resource groups, subsidized emergency childcare, Dependent Care FSA, company events, referral bonuses, and quarterly team-building events.
- 401(k) match, shared ownership employee stock program, and monthly transportation stipend.
- Expected to work in the office five days per week in a standard office setting; limited corporate travel may be required.
Tech Stack
Apache AirflowApache KafkaDockerJavaKubernetesNumPyPandasPythonPyTorchScalascikit-learnSnowflakeSQLTensorFlow
Categories
About PitchBook Data
PitchBook Data builds a subscription platform, datasets, and research that track private and public capital markets for investors, bankers, and corporate development teams. Its products include the PitchBook Platform and API for company, deal, fund, and limited-partner data, plus analyst reports and benchmarks. Founded in 2007 and headquartered in Seattle, it operates as a Morningstar company.