AI/ML Application Developer with Statistical modeling, MS SQL, Python, PyTorch, TensorFlow
Posted 3 days ago by SumasEdge Corporation
Negotiable
Undetermined
Remote
Remote
Summary: The AI Application Developer role focuses on designing, building, and deploying comprehensive AI solutions utilizing machine learning and generative AI techniques. The position requires hands-on experience with data, models, and production systems to create scalable AI applications without relying on code assist tools. Candidates must possess strong skills in machine learning, data engineering, and AI system design. The role emphasizes collaboration with various teams to ensure AI solutions meet enterprise standards.
Key Responsibilities:
- Design, develop, and deploy end to end AI applications from data ingestion to production inference.
- Build data pipelines for data preparation, feature engineering, and model training.
- Select, train, evaluate, and optimize machine learning and deep learning models.
- Develop APIs and services to expose AI models for real time and batch use cases.
- Implement monitoring, logging, and model performance tracking in production.
- Collaborate with product, data, and domain teams to translate business requirements into AI solutions.
- Ensure AI solutions meet enterprise standards for security, scalability, and responsible AI usage.
Key Skills:
- Strong understanding of supervised and unsupervised learning techniques.
- Familiarity with evaluation metrics and model validation techniques.
- Hands on experience with data preprocessing, cleaning, and exploratory data analysis.
- Experience using Python libraries such as Pandas and NumPy, along with SQL.
- Experience building applications using Large Language Models (LLMs).
- Experience integrating LLM APIs into enterprise applications.
- Ability to design scalable AI architectures for training and inference.
- Experience deploying models as APIs or services (e.g., using FastAPI or Flask).
- Strong proficiency in Python.
- Experience with ML/DL frameworks such as PyTorch or TensorFlow.
- Familiarity with REST APIs, microservices, and cloud platforms (Google Cloud Platform).
- Knowledge of model lifecycle management tools (e.g., MLflow preferred).
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Job Title - AI Application Developer
Location - St Louis, MO(Remote)
Must Have - Machine Learning and Statistical modeling, MS SQL, Python, PyTorch, TensorFlow
Job Details:
We are seeking an experienced AI Application Developer / AI Engineer to design, build, and deploy end to end AI solutions using modern machine learning and generative AI techniques. The role involves working hands on with data, models, and production systems to deliver scalable, reliable AI applications without reliance on code assist tools such as GitHub Copilot.
Key Responsibilities
Design, develop, and deploy end to end AI applications from data ingestion to production inference.
Build data pipelines for data preparation, feature engineering, and model training.
Select, train, evaluate, and optimize machine learning and deep learning models.
Develop APIs and services to expose AI models for real time and batch use cases.
Implement monitoring, logging, and model performance tracking in production.
Collaborate with product, data, and domain teams to translate business requirements into AI solutions.
Ensure AI solutions meet enterprise standards for security, scalability, and responsible AI usage.
Required AI Skill Areas (Core 4 Skills)
1. Machine Learning & Model Development
Strong understanding of supervised and unsupervised learning techniques.
Familiarity with evaluation metrics and model validation techniques.
2. Data Engineering & Feature Engineering
Hands on experience with data preprocessing, cleaning, and exploratory data analysis.
Experience using Python libraries such as Pandas and NumPy, along with SQL.
3. Generative AI / LLM Based Application Development
Experience building applications using Large Language Models (LLMs).
Experience integrating LLM APIs into enterprise applications.
4. AI System Design, Deployment & MLOps
Ability to design scalable AI architectures for training and inference.
Experience deploying models as APIs or services (e.g., using FastAPI or Flask).
Technical Skills
Strong proficiency in Python
Experience with ML/DL frameworks such as PyTorch or TensorFlow
Familiarity with REST APIs, microservices, and cloud platforms (Google Cloud Platform)
Knowledge of model lifecycle management tools (e.g., MLflow preferred)