- Company Name
- PitchBook
- Job Title
- Machine Learning Engineer
- Job Description
-
**Job Title:** Machine Learning Engineer
**Role Summary:**
Design, develop, and operationalize AI/ML solutions—primarily NLP, generative AI, and large language models—to extract and deliver actionable insights from structured and unstructured data. Work end‑to‑end on model architecture, training, deployment, and maintenance while collaborating with engineering, data science, and product teams to align technical output with business objectives.
**Expectations:**
- Deliver high‑impact AI features that improve insight generation, speed, and quality.
- Ensure production‑grade reliability, scalability, and efficiency of ML services.
- Contribute to technical excellence through knowledge sharing, code reviews, and mentorship.
- Stay current with emerging GenAI/NLP technologies and translate research into practical implementations.
**Key Responsibilities:**
1. Design, build, and deploy NLP/GenAI models for summarization, semantic search, classification, and prediction.
2. Integrate models into the platform’s AI/ML infrastructure and collaborate with data collection teams to secure high‑quality training data.
3. Optimize model performance, implement monitoring, evaluation, and compliance frameworks for responsible AI use.
4. Develop scalable data pipelines and services using cloud and container technologies.
5. Participate in agile development cycles, contribute to design/architecture decisions, and conduct code and design reviews.
6. Mentor junior engineers, assist in onboarding, and document best practices.
7. Experiment with and evaluate new research, tools, and methodologies to enhance product capabilities.
**Required Skills:**
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face).
- Expertise in NLP techniques, transformers, LLMs, and generative AI models.
- Experience with model serving, CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, GCP, Azure).
- Solid understanding of data engineering concepts, large‑scale data processing, and API development.
- Ability to translate business requirements into technical solutions; strong problem‑solving and communication skills.
- Familiarity with model monitoring, bias mitigation, security, and responsible AI practices.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related field; Master’s preferred.
- Demonstrated experience (3+ years) in machine learning engineering, preferably with a focus on NLP/GenAI.
- Relevant certifications (e.g., AWS Certified Machine Learning – Specialty, Google Professional ML Engineer) are a plus but not mandatory.