TECHNOLOGY PARTNERS INC
Data Scientist / AI-ML Engineer
TECHNOLOGY PARTNERS INC, Maryland Heights, Missouri, United States, 63043
Technology Partners is currently seeking a talented Data Scientist / AI-ML Engineer.
Do you have experience with production‑grade Machine Learning, GenAI agentic workflows, and cloud‑native model deployment?
Let us help you make your next big career move a reality!
What You Will Be Doing: You will serve as a hands‑on Data Scientist with strong AI/ML engineering skills to design and build scalable solutions across multi‑cloud platforms. You will partner with business and engineering teams to translate complex problems into measurable services, including GenAI agents, production ML models, and internal analytical applications. You will be responsible for the full lifecycle—from design and training to deploying CI/CD pipelines and monitoring model performance.
Key Responsibilities:
Partner with business and engineering teams to translate problems into measurable AI/ML solutions and success metrics.
Design, train, validate, and deploy models for classification, regression, recommendation, and time‑series forecasting; pick algorithms, features, and evaluation strategies that match business goals.
Develop and evaluate GenAI agent applications using frameworks like Langchain and Google ADK, leveraging techniques such as RAG, prompt engineering, and vector DB integration.
Build and operate reliable data pipelines and model inference endpoints across GCP and AWS (BigQuery, Vertex AI, Cloud Run, S3, Lambda, SageMaker, etc.).
Implement CI/CD, automated testing, and monitoring for ML/data projects (GitHub Actions, Cloud Build, CodeBuild/CodePipeline).
Create lightweight dashboards and internal apps (Streamlit, Plotly Dash) to deliver models and insights to stakeholders.
Write clear model documentation: problem formulation, modeling approach, validation, data needs, and deployment steps.
Advocate for coding best practices, reproducibility, and shared documentation across a global data science organization.
Required Skills & Experience:
Proficiency in AI/ML engineering, specifically the ability to move beyond research to deploying production‑grade models and GenAI/LLM agentic workflows within cloud environments (GCP/AWS).
Master's degree (plus 1+ years experience) or a PhD in a quantitative field (CS, Data Science, Math/Stats).>
Expert‑level Python and SQL skills.
Proficiency with scikit‑learn, XGBoost/LightGBM, and deep learning frameworks (PyTorch or TensorFlow).
Hands‑on experience with GCP (BigQuery, Vertex AI) and AWS (S3, Lambda, SageMaker).
Solid understanding of AI/ML algorithm theory, statistical assumptions, and computational complexity.
Experience implementing CI/CD pipelines for machine learning (MLOps).
Desired Skills & Experience:
Experience building APIs for model/agent inference.
Knowledge of security and compliance: IAM, secrets management, and VPC/networking.
Experience with containerization (Docker) and workflow orchestration.
Strong background in causal inference or econometrics.
Experience with A/B testing and experimental design.
Pay: $54.60 - $78.00 /hr.
We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to provide sponsorship at this time or accept candidates who would require a corp‑to‑corp agreement.
If this position sounds like you, WE SHOULD TALK!
Your better future is ready, and we want to put the right tools in your hands to get you there. Let's go!
Keywords: Data Scientist, AI Engineer, ML Engineer, Python, SQL, GenAI, LLM, LangChain, RAG, GCP, BigQuery, Vertex AI, AWS, SageMaker
Looking for more opportunities with Technology Partners? Check out technologypartners.net/jobs!
All offers of employment at Technology Partners are contingent upon clear results of a thorough background check and drug screening that meet corresponding laws and regulations at the city, state and federal level.
Pay ranges are influenced by candidate qualifications, experience, and role specifics, with the actual rate determined considering skills, market conditions, and are subject to change by the employer; pay negotiations follow all state and federal legal guidelines.
#J-18808-Ljbffr
Do you have experience with production‑grade Machine Learning, GenAI agentic workflows, and cloud‑native model deployment?
Let us help you make your next big career move a reality!
What You Will Be Doing: You will serve as a hands‑on Data Scientist with strong AI/ML engineering skills to design and build scalable solutions across multi‑cloud platforms. You will partner with business and engineering teams to translate complex problems into measurable services, including GenAI agents, production ML models, and internal analytical applications. You will be responsible for the full lifecycle—from design and training to deploying CI/CD pipelines and monitoring model performance.
Key Responsibilities:
Partner with business and engineering teams to translate problems into measurable AI/ML solutions and success metrics.
Design, train, validate, and deploy models for classification, regression, recommendation, and time‑series forecasting; pick algorithms, features, and evaluation strategies that match business goals.
Develop and evaluate GenAI agent applications using frameworks like Langchain and Google ADK, leveraging techniques such as RAG, prompt engineering, and vector DB integration.
Build and operate reliable data pipelines and model inference endpoints across GCP and AWS (BigQuery, Vertex AI, Cloud Run, S3, Lambda, SageMaker, etc.).
Implement CI/CD, automated testing, and monitoring for ML/data projects (GitHub Actions, Cloud Build, CodeBuild/CodePipeline).
Create lightweight dashboards and internal apps (Streamlit, Plotly Dash) to deliver models and insights to stakeholders.
Write clear model documentation: problem formulation, modeling approach, validation, data needs, and deployment steps.
Advocate for coding best practices, reproducibility, and shared documentation across a global data science organization.
Required Skills & Experience:
Proficiency in AI/ML engineering, specifically the ability to move beyond research to deploying production‑grade models and GenAI/LLM agentic workflows within cloud environments (GCP/AWS).
Master's degree (plus 1+ years experience) or a PhD in a quantitative field (CS, Data Science, Math/Stats).>
Expert‑level Python and SQL skills.
Proficiency with scikit‑learn, XGBoost/LightGBM, and deep learning frameworks (PyTorch or TensorFlow).
Hands‑on experience with GCP (BigQuery, Vertex AI) and AWS (S3, Lambda, SageMaker).
Solid understanding of AI/ML algorithm theory, statistical assumptions, and computational complexity.
Experience implementing CI/CD pipelines for machine learning (MLOps).
Desired Skills & Experience:
Experience building APIs for model/agent inference.
Knowledge of security and compliance: IAM, secrets management, and VPC/networking.
Experience with containerization (Docker) and workflow orchestration.
Strong background in causal inference or econometrics.
Experience with A/B testing and experimental design.
Pay: $54.60 - $78.00 /hr.
We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to provide sponsorship at this time or accept candidates who would require a corp‑to‑corp agreement.
If this position sounds like you, WE SHOULD TALK!
Your better future is ready, and we want to put the right tools in your hands to get you there. Let's go!
Keywords: Data Scientist, AI Engineer, ML Engineer, Python, SQL, GenAI, LLM, LangChain, RAG, GCP, BigQuery, Vertex AI, AWS, SageMaker
Looking for more opportunities with Technology Partners? Check out technologypartners.net/jobs!
All offers of employment at Technology Partners are contingent upon clear results of a thorough background check and drug screening that meet corresponding laws and regulations at the city, state and federal level.
Pay ranges are influenced by candidate qualifications, experience, and role specifics, with the actual rate determined considering skills, market conditions, and are subject to change by the employer; pay negotiations follow all state and federal legal guidelines.
#J-18808-Ljbffr