AI/ML Engineer I

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Astreya

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2001

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Astreya is a leading global provider of IT Managed Services and Technology Solutions, known for its innovative approach to digital engineering and IT logistics. The company focuses on empowering businesses to excel in today's dynamic digital landscape by maximizing productivity and fostering innovation. Astreya offers a range of services including Data Center & Network Management, Digital Workplace Services, Next-Gen Digital Engineering, and Cybersecurity Services. With a commitment to excellence and a focus on operational frameworks, Astreya aims to transform technology into a valuable strategic asset for organizations worldwide.

📋 Description

• Clean, annotate, and pre-process datasets for supervised learning models • Implement simple machine learning models such as logistic regression and decision trees under guidance • Produce exploratory data analysis reports • Document model experiments in Jupyter notebooks • Write and maintain unit-tested ML scripts • Assist with data cleaning, feature engineering, testing basic ML models, and debugging scripts • Develop ML modules, assist in deployment, support data pipelines, and contribute to documentation and unit testing • Support data preparation and model training under guidance • Develop and maintain smaller AI modules such as anomaly detection • Assist in deployments and write technical documentation • Lead development of scalable ML models and integrate them into ITSM systems • Ensure compliance and performance metrics • Architect end-to-end AI platforms and oversee cross-domain projects such as NLP for service desks and computer vision for asset tracking • Participate in code reviews • Build production-grade models • Use MLflow, Airflow, CI/CD tools, and cloud ML services • Deploy and monitor models • Own end-to-end AI/ML solutions including architecture, training, deployment, and monitoring • Apply domain knowledge to improve model relevance, including IT operations and cybersecurity • Understand and apply data engineering best practices

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Science, IT, or a related field • Master’s degree preferred or equivalent experience for senior levels • Knowledge of machine learning techniques including regression, classification, and clustering • Knowledge of deep learning architectures including CNNs, RNNs, Transformers, and LLMs • Knowledge of NLP, including tokenization, BERT, and prompt engineering • Knowledge of Big Data fundamentals, including Spark and Hadoop • Knowledge of model interpretability, AI ethics, and bias detection • Familiarity with cloud-native AI services such as AWS SageMaker, GCP Vertex AI, and Azure ML • Knowledge of data governance, security, and ethical AI practices • Programming skills in Python and Apps Script • Experience with TensorFlow, PyTorch, scikit-learn, and HuggingFace • Experience with Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, and Postman • Data pipeline skills including SQL, Pandas, and data APIs • Deployment experience with Flask/FastAPI, CI/CD, REST APIs, and cloud functions • Strong analytical and debugging skills • Ability to translate business problems and challenges into AI/ML solutions • Ability to communicate technical findings effectively to technical and non-technical stakeholders • Ability to work under Agile or DevOps-based workflows • Ability to stay current with research and emerging technologies • Ability to handle ambiguity and balance research with delivery • Ability to collaborate across globally distributed teams • Familiarity with basic ML/DL principles and AI/ML tools such as Jupyter, scikit-learn, or TensorFlow (basic use) • Bachelor’s degree is the stated minimum educational requirement

🏖️ Benefits

• Learning, collaboration, and career growth opportunities • Inclusive culture where diverse perspectives are valued • Opportunity to make an impact • Global team environment