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Applied Machine Learning Intern Jobs in Tracy, CA

Symhas

GEN AI Lead

Livermore, CA · On-site

Generative AI Lead | 6-8 Years Experience We're looking for a seasoned Machine Learning Engineer ... Applied to NLP, Computer Vision, and Time-Series Forecasting Data Engineering Feature engineering ...

Symhas

GEN AI Lead

Dublin, CA · On-site

Generative AI Lead | 6-8 Years Experience We're looking for a seasoned Machine Learning Engineer ... Applied to NLP, Computer Vision, and Time-Series Forecasting Data Engineering Feature engineering ...

Robert Half

Data Scientist II

San Ramon, CA

D. in Computer Science, Data Science, Machine Learning, or related fields. * 5+ years of experience in applied ML, AI development, or advanced data science roles. * Hands-on experience building and ...

Robert Half

Data Scientist II

San Ramon, CA

D. in Computer Science, Data Science, Machine Learning, or related fields. * 5+ years of experience in applied ML, AI development, or advanced data science roles. * Hands-on experience building and ...

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All JobsApplied Machine Learning Intern JobsApplied Machine Learning Intern Jobs in Tracy, CA

Applied Machine Learning Intern information

See Tracy, CA salary details

$27.4K

$45.8K

$94.7K

How much do applied machine learning intern jobs pay per year?

As of Aug 8, 2026, the average yearly pay for applied machine learning intern in Tracy, CA is $45,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $49,500.00 per year, depending on experience, location, and employer.

What is the difference between Applied Machine Learning Intern vs Data Science Intern?

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

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Applied Machine Learning Intern jobs near you

GEN AI Lead

Symhas

Livermore, CA • On-site

Contractor

Re-posted 5 days ago

Job description

Generative AI Lead | 6–8 Years Experience

We're looking for a seasoned Machine Learning Engineer who thrives at the intersection of data, engineering, and business impact. If you love turning messy real-world problems into production-grade AI solutions — this one's for you.


Work Schedule

This is a contract role requiring 2 days onsite per week. Candidates must be able to commute to the office location.


What You'll Do

  • Partner directly with business stakeholders to define ML use cases, success metrics, and evaluation frameworks — translating strategy into working models
  • Lead end-to-end data workflows: exploration, quality checks, feature engineering, and dataset preparation
  • Build, train, and iterate on ML models; run experiments, compare candidates, and champion the best solution
  • Package and deploy models into production-ready services using containerization and MLOps best practices
  • Own post-deployment health — set up monitoring, track model performance, and drive continuous improvement


Your Technical Toolkit

Languages & Querying Python (hands-on, non-negotiable) · SQL (joins, window functions, CTEs, query optimization)

Machine Learning Regression · Decision Trees · Random Forest · XGBoost · LightGBM · SVM · KNN Model evaluation (Precision/Recall, F1, ROC-AUC, MSE/RMSE) · Hyperparameter tuning · Cross-validation

Deep Learning TensorFlow · Keras · PyTorch · CNNs · RNNs · LSTMs · Transformers Applied to NLP, Computer Vision, and Time-Series Forecasting

Data Engineering Feature engineering · Missing data handling · Outlier detection · Normalization · Data cleaning pipelines

Visualization & BI Matplotlib · Seaborn · Plotly · Tableau · Power BI · Storytelling with data

Cloud & Big Data Spark · Hadoop · AWS (S3, SageMaker, EC2) or Azure (Databricks, Data Factory) or GCP (BigQuery, Vertex AI)

Deployment & MLOps Flask / FastAPI · Docker · Kubernetes (a plus) · CI/CD basics · Airflow / Prefect

Databases MySQL · PostgreSQL · SQL Server · MongoDB · Cassandra


✅ What Sets You Apart

  • A solid conceptual grip on supervised and unsupervised learning, with real experimental work to back it up
  • Proven experience shipping models to production in cloud-agnostic, API-first architectures
  • Comfortable collaborating with engineering teams via version control and CI/CD workflows
  • Generative AI exposure is a strong plus — and increasingly central to this role
Industry
  • Technology, Information and Internet
Employment Type

Contract