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 unit-tested ML scripts • Assist in data cleaning, feature engineering, testing basic ML models, and debugging simple 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 • Attend knowledge sessions • 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 • Document technical solutions and contribute to code reviews • Design and build production-grade models • Use MLflow, Airflow, and CI/CD tools • 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 • Big Data fundamentals, including Spark and Hadoop • Knowledge of model interpretability, AI ethics, and bias detection • Familiarity with cloud-native AI services including AWS SageMaker, GCP Vertex AI, and Azure ML • Knowledge of data governance, security, and ethical AI practices • Programming experience with Python and Apps Script • Familiarity with TensorFlow, PyTorch, scikit-learn, and HuggingFace • Experience with Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, and Postman • Data pipeline skills using SQL, Pandas, and data APIs • Knowledge of 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 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 • Preferred certifications include Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate, Databricks Certified Machine Learning Professional, and Kubernetes or Docker certification for MLOps roles

🏖️ Benefits

• Learning, collaboration, and career growth opportunities • Inclusive culture where diverse perspectives are valued • Opportunity to make an impact • Work with a global team