ML Engineer

Compunnel

$100K — $120K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field
  • Experience with machine learning techniques and algorithms
  • Proficiency in Python or other programming languages used in ML
  • Familiarity with data wrangling and preprocessing techniques
  • Ability to document processes clearly and effectively

Responsibilities

  • Execute data wrangling tasks to create usable datasets
  • Conduct experiments to assess model feasibility and establish baselines
  • Optimize baseline models for peak operational performance
  • Test models based on internal acceptance criteria
  • Document critical artifacts for business communication
  • Collaborate with data scientists for model deployment
  • Coordinate with product teams for new release planning

Benefits

  • Access to advanced tools and technologies
  • Opportunity for mentoring from senior engineers
  • Collaboration with a diverse team of professionals
  • Involvement in innovative projects with real business impact
  • Potential for career growth within the organization
Full Job Description
ML Engineer I
JOB SUMMARY
Under guidance from Senior ML Engineers, develop ML models that provides accurate results with controls to solve the business problem identified, using state of art techniques.

Key Responsibilities
1. Executes relevant data wrangling activities related to the problem in order to create dataset
2. Conduct ML experiments to understand the feasibility and build baseline models to solve the business problem
3. Fine tune the baseline model for optimum performance
4. Test Models internally per acceptance criteria from business
5. Document relevant Artefacts for communicating with the business
6. Work with data scientists to deploy the models.
7. Work with product teams in planning and execution of new product releases.
8. Set OKRs and success steps for self/ team and provide feedback to goals for team members
9. Work with cross functional teams - business, technology, and product teams to understand the product vision; building ML solutions that provides value to the product

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