AI/ML Engineer I

This is a fully remote position, open to applicants in India.

📋 Description

• Clean, annotate, and pre-process datasets for supervised learning models.

• Implement basic machine learning models such as logistic regression and decision trees with guidance.

• Generate exploratory data analysis reports.

• Document model experiments using Jupyter notebooks.

• Create unit-tested ML scripts.

• Assist in data cleaning, feature engineering, testing fundamental ML models, and debugging simple scripts.

• Develop ML modules, aid in deployment, support data pipelines, and contribute to documentation and unit testing.

• Support data preparation and model training with supervision.

• Participate in knowledge-sharing sessions.

• Develop and maintain smaller AI modules, such as anomaly detection.

• Assist in deployments and write technical documentation.

• Lead the development of scalable ML models and integrate them into ITSM systems.

• Ensure compliance and monitor performance metrics.

• Design end-to-end AI platforms and manage cross-domain projects, including NLP for service desks and computer vision for asset tracking.

• Document technical solutions and participate in code reviews.

• Design and build production-grade models.

• Utilize MLflow, Airflow, and CI/CD tools.

• Deploy and monitor models.

• Own comprehensive AI/ML solutions, covering architecture, training, deployment, and monitoring.

• Leverage domain knowledge to enhance model relevance, particularly in IT operations and cybersecurity.

• Comprehend and apply best practices in data engineering.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Data Science, IT, or a related discipline.

• Master’s degree preferred or equivalent experience for senior-level positions.

• Familiarity with machine learning techniques, including regression, classification, and clustering.

• Knowledge of deep learning architectures like CNNs, RNNs, Transformers, and LLMs.

• Understanding of NLP concepts, including tokenization, BERT, and prompt engineering.

• Fundamentals of Big Data, including Spark and Hadoop.

• Awareness of model interpretability, AI ethics, and bias detection.

• Experience 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.

• Familiarity with TensorFlow, PyTorch, scikit-learn, and HuggingFace.

• Experience with Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, and Postman.

• Skills in data pipelines using SQL, Pandas, and data APIs.

• Understanding of Flask/FastAPI, CI/CD, REST APIs, and cloud functions.

• Strong analytical and debugging capabilities.

• Ability to translate business problems into AI/ML solutions.

• Proficiency in communicating technical findings to both technical and non-technical stakeholders.

• Capability to work within Agile or DevOps-based workflows.

• Commitment to staying up-to-date with research and emerging technologies.

• Capacity to navigate 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

• Opportunities for learning, collaboration, and career advancement.

• An inclusive culture that values diverse perspectives.

• Chance to make a significant impact.

• Work within a global team.