Data Science Specialist

Senior Data Science Engineer (AI Systems & Intelligent Automation)

ABOUT BOSENET

Bosenet builds AI-driven meeting intelligence and automated workflow systems for enterprise

environments. We combine advanced data engineering, applied machine learning, and large language

model (LLM) technologies to help organizations transform real-time collaboration and decision-making.

ROLE SUMMARY

We are seeking a Senior Data Science Engineer with 4+ years of industry experience who can

independently lead and execute AI/ML projects end-to-end. This role requires strong technical

ownership, architectural judgment, and the ability to work across data engineering, machine learning,

and production deployment.

KEY RESPONSIBILITIES

AI/ML Project Leadership

Own AI/ML initiatives from problem definition to production deployment.

Drive solution architecture for machine learning, NLP, and LLM-powered workflows.

Define technical milestones, success metrics, and delivery plans.

Machine Learning, NLP & Multimodal AI

Develop models for prediction, classification, recommendation, and text intelligence.

Build and optimize NLP, LLM, and retrieval-augmented generation (RAG) systems.

Work with multimodal AI, including combining audio, text, image, and document understanding.

Apply embeddings, vector databases, CLIP-like models, or VLMs for multimodal tasks.

Computer Vision

Develop and deploy CV models, including classification, detection, segmentation, OCR, and

document intelligence.

Work with CNNs, transformers, and deep vision architectures (e.g., YOLO, DETR, ViT).

Build and manage image/video datasets, labeling workflows, and evaluation pipelines.

Integrate computer vision capabilities with NLP/LLM systems for multimodal intelligence.

Data Engineering & Pipeline Development

Design and maintain scalable ETL/ELT pipelines for structured and unstructured data.

Implement data quality monitoring, validation, and observability.

Work across modern data stacks including Kafka, and cloud platforms.

Production Deployment & MLOps

Deploy, monitor, and maintain machine learning systems in production.

Work with versioning, CI/CD, experiment tracking, and model monitoring tools.

Ensure reliability, reproducibility, and cost efficiency of ML services.

Cross-Functional Collaboration & Leadership

Mentor junior engineers and contribute to team-wide best practices.

Collaborate closely with product, engineering, and research teams.

Provide clear technical documentation and communicate findings to stakeholders.

MINIMUM QUALIFICATIONS

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related discipline.

4+ years of hands-on experience in applied ML, data science, or AI engineering.

Strong proficiency in Python, SQL, and ML frameworks (scikit-learn, PyTorch, TensorFlow).

Experience with data pipelines, feature engineering, and large-scale datasets.

Working knowledge of LLMs, NLP techniques, and vector search.

Experience deploying ML solutions in production environments.

PREFERRED QUALIFICATIONS

Experience mentoring engineers or leading technical initiatives.

Familiarity with Airflow, dbt, Kafka or equivalent data tools.

Knowledge of RAG systems, embeddings, and advanced NLP workflows.

Understanding of data governance, privacy, and secure ML practices.

Experience with model evaluation frameworks and A/B testing.

WHAT SUCCESS LOOKS LIKE

Independent delivery of a high-impact AI/ML project from concept to deployment.

Creation of scalable models and pipelines used across engineering teams.

Demonstrated improvement in AI accuracy, performance, or automation capabilities.

Clear technical communication and consistent cross-team collaboration.

WHY JOIN BOSENET

Work on cutting-edge AI systems powering enterprise meeting intelligence.

Take full ownership of AI/ML solutions used in real-world production environments.

Opportunity to grow into Lead or Staff-level AI engineering roles.

Contribute to building an AI-first platform shaping the future of enterprise collaboration.