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Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
The role involves leading technical evaluations, creating POCs, advising on architecture, and collaborating with sales and support for customer success in the EMEA region.
Top Skills:
APIsDockerJavaScriptKubernetesPythonRustTypescript
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
The Solutions Architect will lead architecture and implementation of enterprise deployments for Deepgram's voice AI solutions, ensuring technical success in post-sales engagements and collaborating with multiple teams to improve customer outcomes.
Top Skills:
DockerHelmJavaScriptKubernetesPythonRust
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Lead complex post-sales engagements as Solutions Architect, focusing on architecture, implementation, and technical support for enterprise customers in APAC. Collaborate closely with various teams to optimize integrations and deliver high customer satisfaction.
Top Skills:
DockerHelmJavaScriptKubernetesPythonTypescript
As a Business Analyst & Data Annotator, you will play a crucial role in gathering and analyzing business requirements, acting as a bridge between stakeholder needs and technical teams. You will also handle the data annotation process, ensuring the production of high-quality, accurately labeled datasets necessary for training machine learning models.
This role involves close collaboration with ML engineers, data scientists, and business teams to ensure that data aligns with project goals. Your work will center on translating complex business needs and technical specifications into clear instructions, managing data labeling workflows, and maintaining data quality standards.
Responsibilities:
- Develop and implement detailed guidelines and instructions for data labeling and annotation to ensure consistency and accuracy across datasets;
- Review and validate labeled data, providing constructive feedback to annotation teams to improve data quality and adherence to project standards;
- Collaborate with data scientists and ML engineers to prepare, organize, and support the creation of high-quality annotated datasets for model training;
- Manage the annotation workflow, prioritize tasks, and track progress to ensure timely delivery of labeled data;
- Maintain high standards of data privacy, security, and compliance throughout all annotation processes;
- Gather and analyze business requirements, workflows, and terminology to understand data needs and improve annotation processes;
- Facilitate communication between technical teams and stakeholders by translating complex technical or domain-specific language into clear, accessible instructions and explanations;
- Offer insights into business processes that could benefit from automation or ML solutions, supporting the design and implementation of such projects;
- Support continuous improvement of data annotation guidelines, workflows, and overall business analysis practices to enhance efficiency and data quality.
Requirements:
- At least 1 year of experience in the relevant role;
- Excellent English language skills (B2 level or higher, ideally C1), especially when working with reports containing complex terminology;
- Strong analytical skills and an understanding of business workflows;
- Attention to detail and ability to create clear instructions and guidelines for annotation teams;
- Understanding of data privacy, security standards, and compliance requirements.
Nice to Have:
- Basic knowledge of machine learning concepts and data management principles;
- Familiarity with ML workflows, data pipelines, and MLOps tools;
- Experience with cloud platforms such as AWS, GCP, or Azure;
- Experience with data labeling or annotation;
- Experience in creating markups for AI;
- Insurance industry background.
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