MTS, Data Infrastructure Engineer

California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI & Machine Learning, Data & AnalyticsIndustries

Requirements

Candidates should have hands-on experience in building distributed systems, including real-time streaming and batch data processing. Proficiency in multiple programming languages relevant for such systems, such as Python, Rust, C++, Go, and Java, is required. Knowledge about deploying and operating high availability production systems in the cloud is essential, along with experience designing service-oriented architectures and leveraging various data store technologies. A strong energy and ambition to build an exceptional product, as well as a growth mindset for continuous improvement, are also expected.

Responsibilities

The Data Infrastructure Engineer will develop solutions to orchestrate and support massive quantities of data through stages like ingestion, indexing/mining, transformation, machine learning, and online deployment. They will create platforms that enable scientists, researchers, and developers to run ML jobs easily and quickly at scale using the latest technologies. Additionally, they will define a consistent continuous integration/deployment model to encourage cross-functional development teams to self-service application unit testing, deployment, and operations. The engineer will also influence and lead cross-functional initiatives to align the team towards commonly used technologies and methodologies.

Skills

Python

Rust

C++

Java

Distributed Systems

Data Orchestration

CI/CD

Cloud Deployment

Architecture Design

Data Store Technologies

Delphina

Machine learning solutions for data analytics

About Delphina

Delphina.ai provides machine learning and data science solutions that help businesses analyze trends and predict future outcomes. Their technology integrates with platforms like Snowflake and BigQuery, allowing clients to deploy data pipelines efficiently. Delphina operates on a software-as-a-service (SaaS) model, enabling clients to subscribe to access its user-friendly platform for creating unique data transformations. The company's goal is to empower organizations to leverage predictive AI for improved decision-making and operational efficiency.

San Francisco, CaliforniaHeadquarters

2023Year Founded

$7.3MTotal Funding

SEEDCompany Stage

Data & Analytics, AI & Machine LearningIndustries

11-50Employees

Benefits

Equity in the company

Medical, dental, and vision insurance

401k

Unlimited Paid Time Off

Top of the line Apple equipment

Free lunch in the office twice a week

Risks

Competition from AI giants like OpenAI and Google threatens market share.

Rapid AI advancements could render Delphina's solutions obsolete without continuous innovation.

Dependence on platforms like Snowflake and BigQuery poses operational risks.

Differentiation

Delphina integrates seamlessly with MLOps platforms like Snowflake and BigQuery.

The platform enables thousands of unique feature transformations from raw data.

Delphina's solutions have improved model performance for clients like Uber and Gopuff.

Upsides

Integration with MLflow and Kubeflow enhances platform flexibility and scalability.

AutoML tools can expand Delphina's customer base to smaller businesses.

Growing demand for explainable AI aligns with Delphina's focus on data transformations.

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