Machine Learning Engineer

Emonics LLC; Houston (TX); On-site; USD 70,000 - 95,000; Full time

Job summary

Emonics LLC seeks an entry-level AI/ML Engineer to help build AI-driven applications and machine learning solutions. You will work with AI models, APIs, and data pipelines to support intelligent systems.

Responsibilities include designing and deploying models, data collection and preprocessing, and building production-ready ML pipelines and APIs. A strong-analytical mindset and knowledge of ML frameworks are essential.

Qualifications

• Proficiency in deploying ML models and APIs; familiarity with MLOps concepts.
• Strong SQL and data processing skills for dataset handling.
• Experience with cloud platforms such as AWS, Azure or Google Cloud.
• Demonstrated analytical thinking and problem-solving abilities.

Responsibilities

• Design, develop, train, and deploy machine learning and AI models.
• Collect, clean, preprocess, and analyze large datasets.
• Build and integrate Generative AI, LLM, NLP, or computer vision solutions where applicable.
• Develop production-ready ML pipelines and APIs.
• Stay current with emerging AI/ML technologies, frameworks, and research.

Skills

Model deployment & MLOps

SQL & data processing

Cloud platforms (AWS/Azure/GC)

Problem solving & analytics

Job description

Artificial Intelligence/Machine Learning Engineer — Entry Level Job Description

We are looking for an Entry-Level AI/ML Engineer to help build AI-driven applications and machine learning solutions. The candidate will work with AI models, APIs, and data pipelines to support intelligent systems.

Responsibilities:

Design, develop, train, and deploy machine learning and AI models.

Collect, clean, preprocess, and analyze large datasets.

Build and integrate Generative AI, LLM, NLP, or computer vision solutions where applicable.

Develop production-ready ML pipelines and APIs.

Stay current with emerging AI/ML technologies, frameworks, and research.

Required Skills:

Understanding of model deployment, APIs, and MLOps.

SQL and data processing.

Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

Strong problem-solving and analytical skills.