Description

Responsibilities

1. Project Scoping:
   - Collaborate with stakeholders to understand the business objectives and goals that could be addressed through machine learning solutions.
   - Work closely with cross-functional teams to define the scope and requirements of the AI models.

2. Data Assessment:
   - Evaluate the availability, quality, and relevance of existing data for model development.
   - Collaborate with data engineers to identify potential data sources and assess data preprocessing needs.

3. Technical Feasibility:
   - Conduct a technical analysis to determine the feasibility of implementing machine learning models based on the identified business requirements.
   - Assess the compatibility of available tools and technologies for model development.

4. Risk Identification:
   - Identify potential challenges, risks, and limitations associated with the development and deployment of machine learning models.
   - Propose mitigation strategies to address identified risks.

5. Prototyping:
   - Develop proof-of-concept models to demonstrate the technical feasibility and potential performance of the proposed machine learning solutions.
   - Iterate on models based on feedback from stakeholders.

6. Documentation:
   - Document findings, technical specifications, and recommendations from the feasibility discovery session.
   - Prepare comprehensive reports for stakeholders, including technical and non-technical audiences.

Qualifications:

1. Education:
   - Master's or Ph.D. in Computer Science, Machine Learning, or a related field.

2. Experience:
   - Proven experience as a Machine Learning Engineer with a focus on model development and deployment.
   - Experience working on end-to-end machine learning projects.

3. Skills:
   - Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
   - Strong programming skills in languages such as Python or R.
   - Excellent analytical and problem-solving abilities.

4. Communication:
   - Strong verbal and written communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.

5. Collaboration:
   - Ability to collaborate effectively with cross-functional teams and stakeholders.

How to Apply:
Interested candidates should submit their resume, a cover letter detailing relevant experience, and examples of previous machine learning projects.