(Senior to Principal) Applied Scientist

Posted 2 days agoViewed

💎 Seniority level: Senior, 3+ years

📍 Location: United States, Canada

💸 Salary: 180000.0 - 250000.0 USD per year

🔍 Industry: Software Development

🏢 Company: Gretel👥 51-100💰 $52,199,996 Series B over 3 years agoArtificial Intelligence (AI)Data Collection and Labeling Machine Learning Privacy Generative AI Information Technology Software

🗣️ Languages: English

⏳ Experience: 3+ years

🪄 Skills: AWSPythonArtificial IntelligenceCloud ComputingData AnalysisDifferential EquationsGCPGitImage ProcessingKerasMachine LearningMLFlowNumpyOpenCVPyTorchAlgorithmsAPI testingAzureData StructuresREST APIPandasTensorflowCommunication SkillsAnalytical SkillsCollaborationAttention to detailExcellent communication skillsResearchA/B testing

Requirements:

3+ years of industry experience in building, training, and fine-tuning Machine Learning models, including defining, vetting, and iterating on metrics and running online controlled experiments (A/B testing, interleaving).
A track record of applied research in AI/ML, as demonstrated by leading research projects, conference presentations, in-depth blog posts, or first author publications.
Profound experience and understanding across advanced models, such as Transformers, LSTMs, GANs, CNNs, and diffusion models.
Extensive experience with ML frameworks such as TensorFlow, HuggingFace, PyTorch, Keras, OpenCV, Fairlearn, or MLflow and Python libraries like Pandas
Programming experience in Python and experience with Cloud providers such as AWS, GCP, and Azure
Builder Mindset - you’ve contributed to open source projects and/or have built your own model, tool, or product.
Excellent communication skills – you will interact with customers and/or assist with community-related events, so we’re extra mindful about verbal and written communication.

Responsibilities:

Explore new applications and techniques within language modeling and generative models for multiple modalities, improving synthetic tabular data generation algorithms, ethical/fair AI, and privacy enhancing technologies.
Actively collaborate with engineering, sales engineering/solutions architects, product, sales, and marketing as a part of the customer-feedback loop to better understand our end-users and use cases to design and build more effective and efficient solutions.
Research, design, and build end-to-end reusable, scalable solutions for our customers and users.
Partner with the sales engineering teams on building complex customer solutions; identify and escalate problems to engineering and support teams.
Plan, build, and facilitate industry-specific use cases, including content creation in the form of workshops, webinars, technical blogs, whitepapers and developer community engagement.
Stay abreast of developments in AI, actively sharing and trying out new approaches.
Mentor colleagues and promote a culture of knowledge sharing.

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