Data Scientist - Generative AI
NEARSOURCE TECHNOLOGIES
Date: 1 day ago
City: Remote, Remote
Contract type: Full time
Remote

100% Remote, Canada (covering EST/PST timezones)
Experience: 4+ Years
Role Summary: NearSource is looking for a Data Scientist - Generative AI with expertise in advanced machine learning, large language models, and scalable data solutions. The selected candidate will design and deploy AI-driven systems for enterprise-grade platforms, collaborating with global teams to deliver impactful innovation.
Key Responsibilities
About NearSource: NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives.
Equal Opportunity Statement: NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.
Experience: 4+ Years
Role Summary: NearSource is looking for a Data Scientist - Generative AI with expertise in advanced machine learning, large language models, and scalable data solutions. The selected candidate will design and deploy AI-driven systems for enterprise-grade platforms, collaborating with global teams to deliver impactful innovation.
Key Responsibilities
- Design and implement scalable machine learning models with a focus on Generative AI and LLMs
- Architect and optimize data pipelines leveraging big data platforms such as Hadoop, Spark, and Hive
- Develop high-quality, well-documented, and production-ready code in Python and related technologies
- Drive experimentation using advanced ML techniques, including classification, clustering, optimization, and dimensionality reduction
- Integrate AI/ML solutions with relational and NoSQL databases for enterprise-scale systems
- Apply data science toolkits (pandas, Jupyter, scikit-learn, TensorFlow) to deliver actionable insights
- Collaborate with cross-functional engineering teams to design and enhance recommender systems and AI-driven protocols
- Leverage cloud computing platforms (AWS, SageMaker) for model training, deployment, and scaling
- Communicate technical findings effectively to both technical and non-technical stakeholders
- MS/PhD in Mathematics, Statistics, Physical Sciences, Computer Science, or related fields
- 4+ years of hands-on experience in designing and deploying ML-based solutions
- Strong proficiency with Python and SQL
- Experience with relational and NoSQL databases
- Expertise in big data platforms (Hadoop, Spark, Hive)
- Proficiency with ML frameworks and toolkits (pandas, Jupyter, scikit-learn, TensorFlow)
- Experience with Generative AI, LLMs (RAG, NLP), and context protocol design
- Ability to write scalable, production-grade, and well-documented code
- Familiarity with AWS cloud services, including SageMaker
- Strong communication skills for technical and non-technical presentations
- Familiarity with MLOps practices for optimizing ML workflows in production
- Experience designing recommender systems for enterprise applications
- Exposure to distributed systems and advanced AI model optimization techniques
- Experience leading research projects with publications in AI/ML domains
- Knowledge of containerization and orchestration (Docker, Kubernetes)
About NearSource: NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives.
Equal Opportunity Statement: NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.
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