Applied Machine Learning (ML) Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home
Parallel Partners · CA, US
18 days agoImpress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Applied Machine Learning (ML) Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home role.
Rezi rewrites your resume against Parallel Partners's job description. Free.
Tailor your resume to this Applied Machine Learning (ML) Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home role.
Rezi rewrites your resume against Parallel Partners's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Applied Machine Learning (ML) Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home posting at Parallel Partners — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Applied Machine Learning (ML) Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home posting at Parallel Partners — free, in seconds.
About the Role
The Applied Machine Learning (ML) Engineer will build and improve Machine Learning (ML) systems that power our AI-native applications. You will work on classification, retrieval, ranking, personalization and evaluation, taking ownership from model development to production deployment. This role is for engineers who enjoy solving practical Machine Learning (ML) problems, improving model quality and shipping reliable systems used by real users. Machine Learning (ML) and Artificial Intelligence (AI) experience are required.
Responsibilities
- Build and improve Machine Learning (ML) models for classification, ranking, retrieval and personalization.
- Develop efficient classifiers and optimize model accuracy, precision, latency and cost.
- Improve search relevance and context retrieval using embeddings, hybrid search and reranking.
- Build personalization models that learn from user behavior while respecting privacy.
- Develop evaluation pipelines, labeled datasets and metrics to measure model quality.
- Fine-tune and adapt existing models when supported by sufficient data.
- Build and maintain Machine Learning (ML) training, inference and deployment pipelines.
- Debug production issues, monitor model performance and ship improvements based on real-world feedback.
Requirements
- Machine Learning (ML) experience is required.
- Artificial Intelligence (AI) experience is required.
- Strong foundations in Machine Learning (ML) and modern neural architectures.
- Hands-on experience building and deploying Machine Learning (ML) models in production.
- Experience in classification, ranking, retrieval, recommendation systems or personalization.
- Understanding of model evaluation, experimentation and performance metrics.
- Comfortable writing production-quality code and working with real-world datasets.
- Able to balance model quality, latency, cost and reliability.
- Strong ownership, problem-solving skills
- MUST BE WILLING TO TAKE A 60 MINUTE CODING ASSESSMENT.
Skills
- Embeddings
- Vector search and ranking models
- Production Machine Learning (ML) systems and inference pipelines
- Python
- PyTorch/JAX
Location
- San Francisco, CA
Work Type
- Work From Home
- Remote
Salary/Compensations
- USD 120000 - USD 160000 - yearly
Benefits
- medical insurance
- Dental
- Vision
- Savings Plan Options
- PTO
Equal Opportunity
- All your information will be kept confidential according to EEO guidelines.