As a Data Science Intern at Enveda, you will join our Data Science team and work on machine learning for mass spectrometry, computational biology, and computational chemistry.
Locations (2)
United States
Canada
Compensation
Compensation per month: US - Masters ($5000 USD), PhD ($6000 USD) & Canada - Masters or PhD ($8500 CAD)
Responsibilities
Learn how to develop data-driven solutions tailored to the drug discovery industry as part of our Data Science team
Collaborate on machine learning for mass spectrometry
Collaborate on computational biology and computational chemistry
Manage and support enterprise database platforms including Oracle, SQL Server, and AWS RDS to ensure high availability and performance, develop automation solutions and collaborate with cross-functional teams to support database deployments and operational stability.
Responsibilities
Provide day-to-day administration and support for Oracle, Client SQL Server, and AWS RDS database environments
Monitor database health, performance, and availability
Investigate and resolve database incidents, problems, and operational issues
Perform root cause analysis and implement corrective actions
Provide end‑to‑end technical leadership for Managed Infrastructure Services, including IPVPN, MIS Network, and MIS Wireless, and support third‑level troubleshooting and automation.
Responsibilities
Provide technical leadership for customer issue resolution
Manage security devices such as VPN, firewall, host intrusion prevention, data loss prevention, anti‑virus and anti‑spam systems
Automate routine L3 network operations using Python, Ansible, or Bash
Design, build, and maintain lightweight automation scripts and API integrations
Provide third‑level support for escalations from MIS Technicians
Requirements
University Degree or College Diploma (Computer Science, Engineering, Programming)
Nice to have: Cisco Certified Networking Professional (CCNP)
Lead the development and validation of Physical AI systems for humanoid and industrial robotics, integrating hardware, mechanical, compute, and software components.
Responsibilities
Contribute to Physical AI technology development for humanoid and industrial robotics
Design, prototype, integrate, and validate humanoid hardware and mechanical subsystems
Develop and evaluate learning‑based perception, planning, control, and manipulation workflows
Develop and maintain virtual system models and robotics hardware and software infrastructure
Evaluate and prototype neuromorphic and ultra‑low‑power computing approaches
Requirements
Master’s degree (PhD preferred) in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science or a closely related field
Business analyst responsible for the delivery, implementation, testing, and ongoing support of Air Canada’s new enterprise fuel management system.
Responsibilities
Lead business-side coordination for the implementation of the new fuel management system
Work with the selected vendor and internal project teams to develop and validate business requirement documents, functional requirements, process flows, user stories, test scripts, and implementation documentation
Represent the Energy team in workshops, design sessions, configuration reviews, system demonstrations, governance meetings, and solution validation activities
Document and validate end-to-end business processes across fuel procurement, pricing, inventory, contracts, invoicing, tax, compliance, accounting, reporting, and analytics
Ensure system design and future-state processes support automation, data integrity, auditability, user efficiency, scalability, and business continuity
Requirements
University degree in Business Administration, Supply Chain, Information Systems, Finance, Engineering, Data Analytics, Computer Science, or a related discipline
Develop and enhance AI agents and orchestration capabilities using Python, LangGraph, and LangChain for a US healthcare client, building scalable AI solutions and collaborating with engineering teams to accelerate innovation.
Compensation
Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, and a relocation program.
Responsibilities
Develop and enhance AI agents and orchestration capabilities using Python, LangGraph, and LangChain.
Build and extend AI-enabled guided workflows and automation capabilities.
Design, develop, and optimize conversational AI and chat-based experiences.
Implement agent planning, orchestration, memory, tool-calling, and response-generation capabilities.
Integrate AI agents and applications with enterprise systems, services, and APIs.
Requirements
Nice to have: Model Context Protocol (MCP)
Nice to have: Agent-to-Agent (A2A) communication
Nice to have: Retrieval-Augmented Generation (RAG)
Senior AI Engineer responsible for developing and enhancing an enterprise AI platform using Python, LangGraph, and LangChain for a US healthcare client.
Compensation
Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, and a relocation program.
Responsibilities
Develop and enhance AI agents and orchestration capabilities using Python, LangGraph, and LangChain.
Build and extend AI-enabled guided workflows and automation capabilities.
Design, develop, and optimize conversational AI and chat-based experiences.
Implement agent planning, orchestration, memory, tool-calling, and response-generation capabilities.
Integrate AI agents and applications with enterprise systems, services, and APIs.
The starting salary range posted for this position is $149,100.00 to $218,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Responsibilities
Partner with enterprise customers to understand technical requirements and business goals.
Design scalable AI solution architectures and guide customers through production deployments.
Build integrations, prototypes, and reusable tools that accelerate customer success.
Lead technical workshops, architecture discussions, and troubleshoot complex production issues.
Collaborate with Product and Engineering teams to share customer feedback and influence future product enhancements.
Requirements
Bachelor's in Computer Science
Nice to have: Deploying or supporting Generative AI, LLM, or Machine Learning applications in production
Nice to have: Experience with Kubernetes, cloud infrastructure, observability, or MLOps
Nice to have: Experience building customer-facing technical solutions or integrations
Nice to have: Experience creating reusable developer tools, frameworks, or open-source contributions
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