About Us:
Datacor is the leading provider of software solutions, including ERP, CRM, Asset Tracking, Simulation and Formulation, to the process manufacturing space. We are on a mission to better equip the industry with software solutions and move it forward by building thoughtful, intuitive products that solve our customers’ most difficult problems.
We are passionate about serving our customers and helping them use data as a competitive advantage. Our customers make products that extend and sustain lives by sanitizing, fertilizing, beautifying, cleaning, and recycling the world we live in. We at Datacor help our customers make those products you use every day more safely, cost effectively and more efficiently through our technology platforms and applications.
The Role:
At our core, we empower our top talent with the autonomy to craft innovative solutions that make a real difference—helping our users become better, faster, smarter, and more efficient. In our working team model, you’ll move fast and continuously deliver cutting-edge features by collaborating with a cross functional team. This approach gives our AI scientists and engineers full ownership—from ideation and research to experimentation and scaling groundbreaking products and services that directly impact our users’ daily operations.
We seek curious, humble, and driven individuals who embrace learning as a fundamental part of their journey. If you’re passionate about pushing AI boundaries and making a meaningful impact alongside a supportive, innovative team, this is the place for you.
Responsibilities:
- Collaborate with stakeholders to identify new AI opportunities and create intelligent AI applications.
- Lead MVP development using a test-and-learn approach with cross-functional teams.
- Iterate from problem framing to prototyping and deploying production-grade solutions.
- Deliver reliable, scalable AI features in production.
- Build prototypes and develop data pipelines for deployment.
- Experiment with generative LLMs to create and enhance generative applications using prompts and user feedback.
- Clearly communicate efforts and impact to both technical and business audiences.
Qualifications:
- Currently enrolled in a Master’s of PhD program in Computational Data Science, Computer Science, Electrical/Computer Engineering, or related fields.
- A self-starter with the ability to work independently and within a team.
- Experience in a professional environment, including prior internship experience is preferred.
- Expertise in the latest Large Language Models (LLMs) and AI advancements.
- Proactive in staying updated with evolving AI trends and new LLM releases.
- Skilled at diagnosing and solving complex, ambiguous problems with curiosity and a product-focused mindset.
- Strong communication and presentation skills, able to convey complex analysis clearly and actionably.
- Results-oriented, creative thinker who takes initiative and delivers practical solutions.
- Committed to inclusivity, respecting diverse perspectives to foster innovation and build great products.
- Proven expertise in implementing and fine-tuning generative AI LLMs, with strong NLP knowledge including embeddings, GPT, and Transformer models.
- Familiarity with cloud computing and AI deployment on AWS or Google Cloud.
- Solid foundation in deep learning, machine learning, statistics, and optimization from coursework or practical experience.
- Proficient in Python & C++/Java programming through academic or work experience.
This is a remote internship with potential travel, depending on location, schedule, and business needs.
EOE Statement:
Datacor is an Equal Opportunity Employer and does not discriminate on the basis or race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic.
Use of AI During Interviews:
At Datacor, we value thoughtful problem-solving and authentic perspectives. To ensure a fair and consistent evaluation process, we ask that candidates do not use generative AI tools or outside assistance during live interviews unless explicitly stated otherwise. We're interested in hearing your experience, your approach, and how you think through challenges.
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