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# AI/ML Engineer

- **Company:** ARSENALTECH LLC
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Computer Vision, Cloud Computing, Continuous Integration, Data Cleansing, Python (Programming Language), Machine Learning, NoSQL, NumPy, Software Tools, Tensorflow, Azure Machine Learning, SQL Databases, Feature Engineering, Pytorch, Large Language Models, Apache Spark, Deep Learning, Pandas, AI Platforms, Scikit Learn, Kubernetes, Optimization Algorithms, HuggingFace, Apache Kafka, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** May 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fdea458ac4b85502

## About the Role

Do you have experience in Version control?, * 3-5 years of experience in machine learning or data science.

 * Proficiency in Python and ML libraries (NumPy, pandas, Scikit-learn, TensorFlow, PyTorch).
 * Strong understanding of statistics, linear algebra, and optimization techniques.
 * Hands-on experience in training, tuning, and evaluating ML/DL models.
 * Familiarity with SQL/NoSQL databases and data pipelines.
 * Experience with version control, CI/CD, and MLOps tools (MLflow, DVC, Kubeflow).
 * Good understanding of API integration for serving models in production.
 * Knowledge of cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI).
 * Experience working in Agile/Scrum environments.

Preferred Qualifications:

 * Experience in NLP, computer vision, or time-series analysis.
 * Knowledge of LLMs (e.g., OpenAI, Gemini, Hugging Face Transformers).
 * Familiarity with data engineering tools (Airflow, Spark, Kafka).
 * Experience with AutoML and model monitoring tools.
 * Certifications in AI/ML, Data Science, or Cloud AI are an advantage.

## Description

We are seeking a passionate AI/ML Engineer to design, develop, and deploy machine learning models that solve real-world problems. The ideal candidate will have strong skills in Python, deep learning frameworks, and MLOps tools, with a good understanding of data pipelines and model lifecycle management., * Design and develop machine learning models and pipelines for classification, regression, and NLP/computer vision tasks.

 * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA).
 * Implement and optimize models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
 * Collaborate with data engineers to build scalable data pipelines.
 * Deploy ML models into production using Docker, Kubernetes, or cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI).
 * Monitor and improve model performance post-deployment (model drift detection, retraining).
 * Work closely with software and product teams to translate business requirements into technical ML solutions.
 * Document model architecture, experiments, and results.


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