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AI/ML Solution Engineer at OncoHealth | JobVerse
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AI/ML Solution Engineer
OncoHealth
Remote
Website
LinkedIn
AI/ML Solution Engineer
United States
Full Time
12 hours ago
No H1B
Apply Now
Key skills
AWS
Azure
Cloud
Docker
ETL
Google Cloud Platform
Java
JavaScript
Jenkins
Kubernetes
NoSQL
Numpy
Pandas
PySpark
Python
PyTorch
Scala
Scikit-Learn
SQL
Tensorflow
C++
C
Go
R
AI
ML
Deep Learning
NLP
Computer Vision
LLM
TensorFlow
scikit-learn
NumPy
Hugging Face
XGBoost
ELT
GCP
Google Cloud
GitHub Actions
GitHub
CI/CD
Communication
About this role
Role Overview
Collaborate with clients to understand business needs and translate them into AI/ML-driven solutions.
Build, fine-tune, and integrate AI/ML models (LLMs, NLP, computer vision, deep learning, traditional ML).
Deliver applications that are reliable, intuitive, and built for long-term value.
Navigate emerging and rapidly changing AI/ML technologies and tools.
Adapt quickly, lead through change, and make confident decisions with limited information.
Recommend modern approaches and innovations in AI/ML.
Ask the right questions to uncover root causes and deliver solutions that solve the real problem.
Dig into data pipelines, model architectures, optimization techniques, and workflows that drive better outcomes.
Architect scalable, maintainable AI/ML solutions that go beyond one-off experiments.
Uphold security, data governance, and best practices in every deployment.
Monitor model performance, retrain when necessary, and implement CI/CD pipelines for continuous improvement.
Help others by guiding team members to elevate technical delivery and AI/ML literacy.
Requirements
Proficiency in Python (required); Java, JavaScript, SQL/NoSQL, and data processing tools (NumPy, Pandas, PySpark).
Understanding of C++, R, Julia, Scala a plus.
Proven experience building and deploying LLM applications, developing agentic workflows, and applying advanced prompting and fine-tuning strategies.
Knowledge of ETL/ELT pipelines, familiarity with big data frameworks, data pipeline tools, SQL/NoSQL
Hands-on experience with model development, training, deployment, and maintenance.
Experience with Scikit-learn, TensorFlow, PyTorch, XGBoost, Hugging Face, and modern architectures (CNNs, RNNs, Transformers).
Experience with CI/CD pipelines, experiment tracking, model monitoring, versioning, and building scalable ETL/data pipelines.
Experience with AWS, Azure, GCP cloud infrastructures.
Containerization and Automation (Docker, Kubernetes, Jenkins, GitHub Actions).
Solid foundations in linear algebra, calculus, probability/statistics; familiarity with responsible AI practices, ethics, bias, and governance a plus.
Excellent communication skills to engage both technical and non-technical stakeholders, with a collaborative, problem-solving mindset.
Tech Stack
AWS
Azure
Cloud
Docker
ETL
Google Cloud Platform
Java
JavaScript
Jenkins
Kubernetes
NoSQL
Numpy
Pandas
PySpark
Python
PyTorch
Scala
Scikit-Learn
SQL
Tensorflow
Apply Now
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