Junior Machine Learning Engineer
Emonics LLC
Los Angeles, CA0–2 yrs1h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 2 years · Bachelor's degree or Master's degree
- Must know
- Data structures & algorithmsStatisticsData analysisPythonSQL
- Nice to have
- Machine learningREST APIsDeep learningNLP
- Work
- On-site in Los Angeles
- Pay
- Not stated by the employer.
- Skill demand
- Python79%Statistics35%Data structures & algorithms23%Data analysis9%of 100 similar entry-level jobs posted in the US this week
- Listed
- Nov 12, 2026 · still open
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About the Role
We are looking for a passionate and motivated Associate Machine Learning Engineer to join our growing AI/ML team. You will work alongside experienced engineers and data scientists to develop, train, evaluate, and deploy machine learning models while contributing to real-world AI-driven projects.
Key Responsibilities
- Assist in developing, training, testing, and optimizing machine learning models.
- Collect, clean, preprocess, and analyze structured and unstructured datasets.
- Implement machine learning algorithms for classification, regression, clustering, and prediction tasks.
- Perform exploratory data analysis (EDA) and feature engineering.
- Evaluate model performance using appropriate metrics and validation techniques.
- Collaborate with cross-functional teams to understand business requirements and develop AI/ML solutions.
- Assist in deploying machine learning models and integrating them into applications or APIs.
- Research emerging technologies, tools, and trends in Artificial Intelligence and Machine Learning.
- Maintain technical documentation and contribute to improving existing ML workflows.
Requirements & Tech Stack
- Strong programming knowledge in Python.
- Understanding of fundamental machine learning algorithms and concepts.
- Basic understanding of statistics, probability, and linear algebra.
- Knowledge of data preprocessing, feature engineering, and model evaluation.
- Familiarity with SQL and database concepts.
- Good analytical, logical reasoning, and problem-solving skills.
- Strong communication skills and willingness to learn new technologies.
- Good to Have: Basic knowledge of Deep Learning and Neural Networks.
- Good to Have: Familiarity with NLP, Computer Vision, or Generative AI.
- Good to Have: Understanding of REST APIs and Flask/FastAPI.
- Good to Have: Familiarity with Git, GitHub, and basic cloud platforms.
- Good to Have: Academic projects, internships, or personal projects related to AI/ML.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or a related field.