- Company Name
- Medpace
- Job Title
- AI Engineer
- Job Description
-
Job Title: AI Engineer
Role Summary:
Design, develop, and deploy AI-driven solutions—particularly NLP, large language models (LLM), and intelligent automation—to accelerate clinical research workflows. Lead end‑to‑end ML pipelines, from data acquisition and preprocessing to model training, fine‑tuning, and production deployment, while collaborating with cross‑functional teams to translate business needs into actionable AI systems.
Expectations:
- Deliver high‑quality, production‑ready AI models that meet defined performance and latency targets.
- Scale and maintain ML infrastructure to support continuous learning and model updates.
- Communicate technical concepts effectively to non‑technical stakeholders and provide training or guidance when necessary.
Key Responsibilities:
- Research, architect, and implement machine learning algorithms for classification, regression, clustering, anomaly detection, and recommendation tasks.
- Fine‑tune LLMs and develop interactive AI applications, integrating them with existing IT systems.
- Collect, clean, engineer features for, and curate large datasets for generative and discriminative model training.
- Experiment with supervised, unsupervised, semi‑supervised, reinforcement, and deep learning techniques to optimize model performance.
- Design and automate ML pipelines, encompassing data ingestion, feature engineering, model selection, hyper‑parameter tuning, and validation procedures.
- Build and manage scalable ML infrastructure (e.g., containerized deployments, GPU clusters, model registries) for training, testing, and production use.
- Partner with data stewards, domain experts, and IT teams to ensure data quality, ethical compliance, and system reliability.
Required Skills:
- Strong programming in Python; proficiency with TensorFlow, PyTorch, or equivalent deep learning frameworks.
- Hands‑on experience with NLP technologies (tokenizers, embeddings, transformer models) and LLM fine‑tuning.
- Knowledge of machine learning pipelines, MLOps principles, and cloud or on‑prem deployment strategies.
- Excellent analytical and problem‑solving abilities; meticulous attention to detail.
- Effective communication skills for cross‑team collaboration and documentation.
- Up‑to‑date with latest AI research, trends, and best practices.
Required Education & Certifications:
- Bachelor’s degree in Artificial Intelligence, Computer Science, Data Science, or related field (Master’s preferred).
- Minimum of 1 year of graduate‑level experience implementing and fine‑tuning LLMs or interactive AI applications.
- Relevant certifications in machine learning, NLP, or cloud AI services are advantageous but not mandatory.
Cincinnati, United states
On site
Fresher
05-10-2025