Role:Architect Machine Learning

Experience Level:10+ yrs

Work Location:USA - Remote

Role Overview:

As an ATA Machine Learning Engineer in healthcare, you'll deliver multi-geography projects, empowering healthcare organizations with data ingestion, cloud services, and DevOps. You'll collaborate with Cloud, Software, and Data Engineering teams to build platforms and solutions for digital diagnosis, software as a medical product, and AI marketplaces. 

Key Responsibilities:

• Apply GenAI and LLM-based ML/AI techniques to develop, scale, and integrate model systems and solutions into large-scale cloud-based SaaS production environments for healthcare.

• Design, build, and evaluate solutions for healthcare use cases (e.g., predictive models, summarization, semantic search), performing research, experimentation, data management, and model evaluation.

• Develop high-level solution architectures, collaborating with offshore big-data engineers and decision science analysts to build, test, and assess models predicting and optimizing client business outcomes.

• Ensure responsible AI practices, including quality, fairness, and safety, using frameworks like LLM-as-judge, RAGAS, and LangSmith.

• Translate complex insights into simple, quantifiable business impacts for clients, cultivating deep relationships by understanding their needs.

• Lead technical discussions on architecture design and troubleshooting with clients, proactively providing solutions, and mentor senior resources/team leads.

• Collaborate across functions (product, clinical, data science, engineering) and with offshore delivery managers to ensure seamless communication and delivery.

• Contribute to a collaborative team culture, sharing knowledge, and identifying sales opportunities.

Basic Qualifications:

Must have:

• Ph.D grad, with 1+ years related industry experience OR Masters grad with 4+ years industry experience--including at least 1 year directly related to healthcare ML/AI

• Proven industry experience through multiple major product releases in a commercial SaaS environment.

• Hands-on experience working with healthcare data (e.g. EHR, ADT, clinical notes).

• Proficiency in Python. Proficiency in Java or other languages is helpful.

• Proficiency with SQL and data engineering for AI/ML applications.

• Experience working with large datasets using big data frameworks (e.g. Azure Data Lake, Apache Spark or Databricks)

• Solid understanding of transformer models and LLM-based approaches, including hands-on experience with prompt tuning and PEFT methods (e.g. LoRA, QLoRA) using frameworks such as Hugging Face Transformers.

• Experience building and evaluating models using modern ML packages such as NumPy, SciPy, Pandas, Scikit-learn, PyTorch, and LightGBM.

• Experience building and deploying models using public cloud infrastructure (Azure, AWS, or Google Cloud), including familiarity with version control, CI/CD pipelines, and scaling considerations for production ML systems at SaaS scale.

• Strong communication and collaboration skills; comfortable working on a distributed team.

• Experience with one or more of: reinforcement learning or RLHF, NLP techniques for summarization, extraction, classification, or semantic search, retrieval-augmented generation (RAG) pipelines and/or agentic frameworks (e.g. LangChain, LlamaIndex).

Leadership qualities

• Provide thought leadership to the team and bring industry best practices to the project.

• Ability to lead technology teams and provide them mentorship / support to accelerate performance. 

• Ability to handle conflicts effectively  by managing internal and external stakeholders

• Experience in leading multiple large projects as well as a deep understanding of Agile developments

• Effective communication with all the stakeholders involved.

• communicate clearly about complex subjects and technical plans with technical and non technical audiences.

Good to have:

• Hands-on experience with statistical tools and techniques

• Experience with Agile/Scrum/DevOps software development methodologies.

• Critical eye for the quality of data and strong desire to get it right.

Other Qualifications (OQs):

• Effective communication with all the stakeholders involved

• Need to communicate clearly about complex subjects and technical plans

• Ability to mentor and groom junior members of the team and provide them with guidance and roadmap. 

• Must also have the ability to interact with other members of the team (Juniors, Seniors, ATA, TA, BA, etc) to get their designs from concept to development

• Keeping various audiences in mind, engineers must write their reports in clear language accessible to all.

What’s in it for YOU at Quantiphi:

• Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.

• Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.

• Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.

• Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.