ML Engineer
TalentBridge
•
Atlanta, GA
0
0
0
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Entry level
Posted April 3, 2026
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Responsibilities
Commitments
Responsibilities
- Develop and implement machine learning models and solutions to address business and operational challenges.
- Collaborate with engineering teams, stakeholders, and business partners to understand requirements and translate them into technical solutions.
- Analyze complex datasets to identify insights and opportunities for optimization.
- Design and build scalable ML systems and data-driven applications.
- Participate in technical discussions, code reviews, and architecture decisions.
- Work effectively in environments with ambiguity and evolving requirements .
- Maintain strong collaboration with cross-functional teams.
Commitments
Professional stability and commitment to team success Team Environment This team operates in a consultative engineering culture , emphasizing collaboration, resilience, and continuous learning.
Team members are expected to maintain a constructive attitude while working through complex technical challenges.
MLE II: Early career professionals (2–4 years experience)
Not Met Priorities
What still needs stronger evidence
Requirements
- Coursework or academic experience in Machine Learning .
- Programming experience in modern development languages commonly used for ML and data applications.
- Strong analytical and problem-solving abilities.
- Ability to communicate technical concepts clearly with both technical and non-technical stakeholders.
- Ability to work through ambiguous or evolving problems
- Proven track record of learning quickly and solving difficult technical challenges
- MLE I: Entry-level or recent graduates with internships
- MLE II: Early career professionals (2–4 years experience)
- Senior MLE: Experienced engineers (4–6 years experience)
Preferred Skills
- Recent graduates with strong internships or project experience in machine learning.
- Up to 5–6 years of professional experience in machine learning, data science, or software engineering.
- Experience building or deploying machine learning models in production environments.
- Candidates from strong technical universities or engineering programs.
- Demonstrated ability to quickly learn new technologies and solve complex problems.
- Strong communication and collaboration skills
- Ability to work through ambiguous or evolving problems
- Proven track record of learning quickly and solving difficult technical challenges
Education
- (Not required) – This role is ideal for candidates ranging from recent graduates with strong internships to professionals with up to 5–6 years of experience .
- (Not required) – Bachelor's degree in Computer Science, Computer Engineering, Engineering, or a related technical field .
- (Not required) – Coursework or academic experience in Machine Learning .
- (Not required) – Candidates from strong technical universities or engineering programs.
- (Not required) – MLE I: Entry-level or recent graduates with internships
Job Description Job Title: Machine Learning Engineer (MLE I / MLE II / Senior) Location: United States (Team supporting The Home Depot) Employment Type: Full-time or Contract (potential contract-to-hire) Position Overview We are seeking a Machine Learning Engineer to join a collaborative engineering team focused on solving complex business problems through data science and machine learning. This role is ideal for candidates ranging from recent graduates with strong internships to professionals with up to 5–6 years of experience . The team operates in a highly consultative and collaborative environment , working through ambiguous and complex problems while partnering closely with internal stakeholders. Successful candidates will demonstrate strong technical skills, communication abilities, and a positive, solution-oriented mindset. Key Responsibilities
Develop and implement machine learning models and solutions to address business and operational challenges.
Collaborate with engineering teams, stakeholders, and business partners to understand requirements and translate them into technical solutions.
Analyze complex datasets to identify insights and opportunities for optimization.
Design and build scalable ML systems and data-driven applications.
Participate in technical discussions, code reviews, and architecture decisions.
Work effectively in environments with ambiguity and evolving requirements .
Maintain strong collaboration with cross-functional teams. Basic Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Engineering, or a related technical field .
Coursework or academic experience in Machine Learning .
Programming experience in modern development languages commonly used for ML and data applications.
Strong analytical and problem-solving abilities.
Ability to communicate technical concepts clearly with both technical and non-technical stakeholders. Preferred Qualifications
Recent graduates with strong internships or project experience in machine learning.
Up to 5–6 years of professional experience in machine learning, data science, or software engineering.
Experience building or deploying machine learning models in production environments.
Candidates from strong technical universities or engineering programs.
Demonstrated ability to quickly learn new technologies and solve complex problems. Ideal Candidate Profile The ideal candidate will demonstrate:
Strong communication and collaboration skills
Ability to work through ambiguous or evolving problems
Positive and resilient mindset
Proven track record of learning quickly and solving difficult technical challenges
Professional stability and commitment to team success Team Environment This team operates in a consultative engineering culture , emphasizing collaboration, resilience, and continuous learning. Team members are expected to maintain a constructive attitude while working through complex technical challenges. Experience Level Candidates may fall within one of the following levels:
MLE I: Entry-level or recent graduates with internships
MLE II: Early career professionals (2–4 years experience)
Senior MLE: Experienced engineers (4–6 years experience)
Develop and implement machine learning models and solutions to address business and operational challenges.
Collaborate with engineering teams, stakeholders, and business partners to understand requirements and translate them into technical solutions.
Analyze complex datasets to identify insights and opportunities for optimization.
Design and build scalable ML systems and data-driven applications.
Participate in technical discussions, code reviews, and architecture decisions.
Work effectively in environments with ambiguity and evolving requirements .
Maintain strong collaboration with cross-functional teams. Basic Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Engineering, or a related technical field .
Coursework or academic experience in Machine Learning .
Programming experience in modern development languages commonly used for ML and data applications.
Strong analytical and problem-solving abilities.
Ability to communicate technical concepts clearly with both technical and non-technical stakeholders. Preferred Qualifications
Recent graduates with strong internships or project experience in machine learning.
Up to 5–6 years of professional experience in machine learning, data science, or software engineering.
Experience building or deploying machine learning models in production environments.
Candidates from strong technical universities or engineering programs.
Demonstrated ability to quickly learn new technologies and solve complex problems. Ideal Candidate Profile The ideal candidate will demonstrate:
Strong communication and collaboration skills
Ability to work through ambiguous or evolving problems
Positive and resilient mindset
Proven track record of learning quickly and solving difficult technical challenges
Professional stability and commitment to team success Team Environment This team operates in a consultative engineering culture , emphasizing collaboration, resilience, and continuous learning. Team members are expected to maintain a constructive attitude while working through complex technical challenges. Experience Level Candidates may fall within one of the following levels:
MLE I: Entry-level or recent graduates with internships
MLE II: Early career professionals (2–4 years experience)
Senior MLE: Experienced engineers (4–6 years experience)