Key Deliverables
Cleaned, annotated, and pre-processed datasets for supervised learning models
Simple machine learning models (e.g., logistic regression, decision trees) implemented under guidance
Exploratory data analysis reports
Jupyter notebooks documenting model experiments
Unit-tested ML scripts
Essential Duties and Responsibilities (All Levels):
Assist in data cleaning, feature engineering, testing basic ML models, write and debug simple scripts
Develop ML modules, assist in deployment, support data pipelines, contribute to documentation and unit testing
Support data preparation, model training under guidance, debug code, attend knowledge sessions
Develop and maintain smaller AI modules (e.g., anomaly detection), assist in deployments, write technical documentation
Lead development of scalable ML models, integrate into ITSM systems, ensure compliance and performance metricsArchitect end-to-end AI platforms, oversee cross-domain projects (e.g., NLP for service desk, CV for asset tracking)
Education and/or Work Experience Requirements:
Minimum Requirements:
Bachelor’s degree in Computer Science,Data Science, IT, or a related field.Master’s preferred or equivalent experience for senior levels
Preferred Certifications (All Levels):
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
Kubernetes or Docker certification for MLOps roles
Knowledge, Skills & Abilities (KSAs):
Machine Learning techniques (regression, classification, clustering)
Deep Learning architectures (CNNs, RNNs, Transformers, LLMs)
NLP (tokenization, BERT, prompt engineering)
Big Data fundamentals (Spark, Hadoop)
Model interpretability, ethics in AI, bias detection
Cloud-native AI services (AWS Sagemaker, GCP Vertex AI, Azure ML)
Data governance, security, and ethical AI practices
Programming: Python, Apps Script
Frameworks: TensorFlow, PyTorch, scikit-learn, HuggingFace
Tools: Git, Docker, Kubernetes, Airflow, MLflow,Jupyter, Postman
Data pipeline skills: SQL, Pandas, data APIs
Deployment: Flask/FastAPI, CI/CD, REST APIs, cloud functions
Strong analytical and debugging skills
Translate business problems into AI solutions
Communicate effectively with technical and non-technical stakeholders
Work under Agile or DevOps-based workflows
Stay current with research and emerging technologies
Rapidly learn new AI concepts and tools
Translate business challenges into ML solutions
Communicate technical findings to non-technical stakeholders
Handle ambiguity and balance research with delivery
Collaborate across globally distributed teams
Technical Expertise
Understands basic ML/DL principles
Codes in Python/Apps Script
Familiarity with AI/ML tools such as Jupyter, scikit-learn, or TensorFlow (basic use)
Applies supervised/unsupervised ML methods
Proficient in TensorFlow/PyTorch
Uses cloud ML services
Familiar with ML pipelines
Documents technical solutions and contributes to code reviews
Designs and builds production-grade models
Uses MLflow, Airflow, CI/CD tools
Experience with model deployment and monitoring
Owns end-to-end AI/ML solutions including architecture, training, deployment, and monitoring
Applies domain knowledge to improve model relevance (e.g., IT ops, cybersecurity)
Understands data engineering best practices
Bachelor’s degree in computer science, data science, IT, or related field; Python and Apps Script programming; familiarity with machine learning, data pipelines, cloud ML services, and AI/ML tools.
Key Responsibilities
- cleaning datasets
- building models
- documenting experiments
Skills & Tools
Python, Apps Script, TensorFlow, PyTorch, scikit-learn, HuggingFace, Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, Postman, SQL, Pandas, Flask, FastAPI, CI/CD, REST APIs, AWS Sagemaker, GCP Vertex AI, Azure ML, Spark, Hadoop, BERT
Job Details
- Category: Software Development
- Seniority: Entry Level
- Commitment: Full Time
- Workplace: Remote — India
- Languages: English
About Astreya
A global managed IT services provider delivering human-centered solutions across digital workplace, cloud, data, artificial intelligence, and enterprise platforms. — Industry: Information Technology