AI Engineer
Apply NowCompany: My3Tech
Location: Madison, WI 53711
Description:
Key Responsibilities:
Work closely with data science, engineering teams, and Front Office staff to design and implement AI solutions on Azure.
Develop and deploy containerized solutions for AI deployments utilizing GitLab CI/CD pipelines.
Advise on best practices for building scalable, secure, and efficient AI solutions. Initial focus will be delivering outcomes focused on retrieval-augmented generation (RAG).
Fine-tune existing large language models (LLMs).
Leverage financial data to develop predictive models, risk models, and other solutions that support investment decision-making.
Assist in optimizing Azure infrastructure for performance and cost efficiency.
Integrate AI models and tools into existing systems.
Provide strategic guidance on AI and machine learning.
Mentor and coach internal staff, helping them build proficiency with Azure AI tools and best practices.
Lead training sessions and workshops to develop internal capabilities and foster a culture of continuous learning.
Qualifications:
Minimum of 3 years of experience in AI engineering, with a focus on the Azure ecosystem.
Previous experience in the asset management industry is required.
Proficiency in Python and other relevant programming languages for AI development.
Strong understanding of cloud architecture, data engineering, and containerization technologies (e.g., Docker, Kubernetes).
Experience in the full machine learning lifecycle, from data collection to model deployment and monitoring.
Solid knowledge of financial markets, asset management, and financial data (e.g., time series analysis, portfolio management, risk modeling).
Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Proven experience mentoring
Required Skills : Key Responsibilities: Work closely with data science, engineering teams, and Front Office staff to design and implement AI solutions on Azure. Develop and deploy containerized solutions for AI deployments utilizing GitLab CI/CD pipelines. Advise on best practices for building scalable, secure, and efficient AI solutions. Initial focus will be delivering outcomes focused on retrieval-augmented generation (RAG). Fine-tune existing large language models (LLMs). Leverage financial data to develop predictive models, risk models, and other solutions that support investment decision-making. Assist in optimizing Azure infrastructure for performance and cost efficiency. Integrate AI models and tools into existing systems. Provide strategic guidance on AI and machine learning. Mentor and coach internal staff, helping them build proficiency with Azure AI tools and best practices. Lead training sessions and workshops to develop internal capabilities and foster a culture of continuous learning. Qualifications: Minimum of 3 years of experience in AI engineering, with a focus on the Azure ecosystem. Previous experience in the asset management industry is required. Proficiency in Python and other relevant programming languages for AI development. Strong understanding of cloud architecture, data engineering, and containerization technologies (e.g., Docker, Kubernetes). Experience in the full machine learning lifecycle, from data collection to model deployment and monitoring. Solid knowledge of financial markets, asset management, and financial data (e.g., time series analysis, portfolio management, risk modeling). Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders. Proven experience mentoring
Basic Qualification :
Additional Skills :
Background Check : Yes
Drug Screen : Yes
Notes :
Selling points for candidate :
Project Verification Info :The information provided below is for Apex Systems AV use only and is not to be distributed publicly, or to any third party. Any distribution of the below information will result in corrective action from Apex Systems Vendor Management. MSA: Blanket Approval Received Client Letter: Will Provide
Candidate must be your W2 Employee :No
Exclusive to Apex :No
Face to face interview required :No
Candidate must be local :No
Candidate must be authorized to work without sponsorship ::No
Interview times set : :No
Type of project :
Master Job Title :
Branch Code :
Work closely with data science, engineering teams, and Front Office staff to design and implement AI solutions on Azure.
Develop and deploy containerized solutions for AI deployments utilizing GitLab CI/CD pipelines.
Advise on best practices for building scalable, secure, and efficient AI solutions. Initial focus will be delivering outcomes focused on retrieval-augmented generation (RAG).
Fine-tune existing large language models (LLMs).
Leverage financial data to develop predictive models, risk models, and other solutions that support investment decision-making.
Assist in optimizing Azure infrastructure for performance and cost efficiency.
Integrate AI models and tools into existing systems.
Provide strategic guidance on AI and machine learning.
Mentor and coach internal staff, helping them build proficiency with Azure AI tools and best practices.
Lead training sessions and workshops to develop internal capabilities and foster a culture of continuous learning.
Qualifications:
Minimum of 3 years of experience in AI engineering, with a focus on the Azure ecosystem.
Previous experience in the asset management industry is required.
Proficiency in Python and other relevant programming languages for AI development.
Strong understanding of cloud architecture, data engineering, and containerization technologies (e.g., Docker, Kubernetes).
Experience in the full machine learning lifecycle, from data collection to model deployment and monitoring.
Solid knowledge of financial markets, asset management, and financial data (e.g., time series analysis, portfolio management, risk modeling).
Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Proven experience mentoring
Required Skills : Key Responsibilities: Work closely with data science, engineering teams, and Front Office staff to design and implement AI solutions on Azure. Develop and deploy containerized solutions for AI deployments utilizing GitLab CI/CD pipelines. Advise on best practices for building scalable, secure, and efficient AI solutions. Initial focus will be delivering outcomes focused on retrieval-augmented generation (RAG). Fine-tune existing large language models (LLMs). Leverage financial data to develop predictive models, risk models, and other solutions that support investment decision-making. Assist in optimizing Azure infrastructure for performance and cost efficiency. Integrate AI models and tools into existing systems. Provide strategic guidance on AI and machine learning. Mentor and coach internal staff, helping them build proficiency with Azure AI tools and best practices. Lead training sessions and workshops to develop internal capabilities and foster a culture of continuous learning. Qualifications: Minimum of 3 years of experience in AI engineering, with a focus on the Azure ecosystem. Previous experience in the asset management industry is required. Proficiency in Python and other relevant programming languages for AI development. Strong understanding of cloud architecture, data engineering, and containerization technologies (e.g., Docker, Kubernetes). Experience in the full machine learning lifecycle, from data collection to model deployment and monitoring. Solid knowledge of financial markets, asset management, and financial data (e.g., time series analysis, portfolio management, risk modeling). Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders. Proven experience mentoring
Basic Qualification :
Additional Skills :
Background Check : Yes
Drug Screen : Yes
Notes :
Selling points for candidate :
Project Verification Info :The information provided below is for Apex Systems AV use only and is not to be distributed publicly, or to any third party. Any distribution of the below information will result in corrective action from Apex Systems Vendor Management. MSA: Blanket Approval Received Client Letter: Will Provide
Candidate must be your W2 Employee :No
Exclusive to Apex :No
Face to face interview required :No
Candidate must be local :No
Candidate must be authorized to work without sponsorship ::No
Interview times set : :No
Type of project :
Master Job Title :
Branch Code :