What are the responsibilities and job description for the Machine Learning Engineer / Data Scientist AI/ML position at USEReady?
Job Details
Job Location: Alpharetta, GA (5 days onsite)
Job Title: Job Title: Machine Learning Engineer / Data Scientist AI/ML Innovation and Governance
Duration: Long term Contract / CTH
Target Start Date: ASAP
Below is the update from client on 3/19 regarding the required skills
- ML Modules Fraud detection, sales, Anomaly detection and forecasting
- Create and maintain of ML models
- Ability to detect outage through ML modules
- AI Ops
- Splunk, Servicenow , Databricks, snowflake
- predictive maintenance, Data engineering
Hope you can handle all the below. Please confirm
- ML Engineering (need deep hands on skills), with day to day firefighting skills
- Customer will throw ML issues and s/he has to solve them on the fly
- Has to be able to support day to day firefighting of issues of ML models
- Assist with instant help on ML related issues when needed
- How to train and optimize a model
- Needs to be handson
- OK with 4-5 yrs of experience but needs to be able to work on the ground from Day1
- Cloud platforms run ML models Fraud detection, sales, Anomaly detection and forecasting like ML Models Risk Tolerance or CICIL reporting
- During business systems go down - so leverage the platform and build ML model leveraging the platform. ML model should have intelligence to detect outage or forecast (AIOps
Job Description:
We are seeking a highly skilled and motivated Machine Learning Engineer/Data Scientist with expertise in data science, machine learning, and AI/ML model optimization. The ideal candidate will have a strong foundation in improving model efficiencies, a passion for innovation in MLOps (Machine Learning Operations), and a deep understanding of AI/ML governance frameworks.
This role requires someone who is not only technically proficient but also eager to learn new skills, embrace challenges, and thrive in a fast-paced, collaborative environment. You will be part of a global team, working on projects that push the boundaries of AI/ML capabilities while ensuring robust governance and ethical practices.
Key Responsibilities:.
- Design, develop, and optimize machine learning models to improve efficiency, scalability, and performance.
- Implement innovative MLOps practices to streamline model deployment, monitoring, and maintenance.
- Collaborate with cross-functional teams to integrate AI/ML solutions into business processes.
- Develop and enforce governance frameworks for AI/ML systems, ensuring compliance with ethical and regulatory standards.
- Stay updated on the latest advancements in AI/ML technologies and incorporate them into existing workflows.
- Conduct research and experimentation to identify new approaches for improving model performance and efficiency.
- Document and communicate technical concepts and solutions to both technical and non-technical stakeholders.
- Mentor and guide junior team members, fostering a culture of continuous learning and innovation.
Required Skills and Qualifications:
- Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Proven experience in data science, machine learning, and AI model development.
- Strong knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, TensorFlow Extended).
- Proficiency in programming languages such as Python, R, or Java.
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and containerization technologies (e.g., Docker, Kubernetes).
- Familiarity with AI/ML governance frameworks and ethical AI practices.
- Excellent problem-solving skills and the ability to handle complex, ambiguous challenges.
- Strong communication and collaboration skills, with the ability to work in a global team environment.
Desired Attributes:
- A growth mindset with a willingness to learn new skills and adapt to evolving technologies.
- Ability to handle steep learning curves and thrive in dynamic, fast-paced environments.
- Passion for innovation and a proactive approach to identifying and solving problems.
- Experience working in a global or distributed team is a plus.
