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Ai Data Training Jobs (NOW HIRING)

Schonfeld

AI Data Engineer

New York, NY · On-site

$125K - $150K/yr

Implement data versioning, lineage tracking, and observability for AI training and inference pipelines. * Optimize data delivery for low-latency AI interactions and high-throughput batch processing.

Innovative Solutions

AI Data Architect

Rochester, NY · Remote

$150K - $200K/yr

As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS -- from S3 ... Design SageMaker ML pipelines for training, Model Registry, and inference * Lead data discovery ...

Schonfeld

AI Data Engineer

New York, NY · On-site

$125K - $150K/yr

Implement data versioning, lineage tracking, and observability for AI training and inference pipelines. * Optimize data delivery for low-latency AI interactions and high-throughput batch processing.

Innovative Solutions

AI Data Architect

Rochester, NY · On-site +1

$150K - $200K/yr

As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS - from S3 ... Design SageMaker ML pipelines for training, Model Registry, and inference * Lead data discovery ...

Hp

AI Data Scientist

Spring, TX · On-site

$130K - $205K/yr

We also serve as HP's AI Center of Excellence, providing consulting assistance, reuseable components and frameworks, and training to other teams across the company. As a Data Scientist focused on ...

eTeam

AI & Data - Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

... training and inference. • Implement data quality tests, documentation, and lineage in DBT • ... AI/Data Science) team to provide feature ready datasets. Qualifications : Required : • Hands-on ...

Rosnet LLC

AI Data Engineer

Kansas City, MO · On-site

$102K - $123K/yr

Develop and maintain MLOps infrastructure including model training pipelines, versioning ... Relevant certifications in cloud platforms, data engineering, or AI/ML (e.g., Azure Data Engineer ...

HP Development Company, L.P.

AI Data Scientist

Spring, TX · On-site

$130K - $205K/yr

We also serve as HP's AI Center of Excellence, providing consulting assistance, reuseable components and frameworks, and training to other teams across the company. As a Data Scientist focused on ...

C the Signs

AI Data Engineer

Boston, MA · Remote

$117K - $140K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

Rosnet LLC

AI Data Engineer

Kansas City, MO · On-site

$102K - $123K/yr

Develop and maintain MLOps infrastructure including model training pipelines, versioning ... Relevant certifications in cloud platforms, data engineering, or AI/ML (e.g., Azure Data Engineer ...

C the Signs

AI Data Engineer

Boston, MA · On-site +1

$124K - $149K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

Quantifind

AI Data Engineer

Palo Alto, CA · On-site

$134K - $161K/yr

You pair traditional technical training with a forward-leaning approach to agentic coding, rapid ... Quantifind is a data science technology company whose AI platform uncovers signals of risk across ...

Quantifind

AI Data Engineer

Palo Alto, CA · On-site

$134K - $161K/yr

You pair traditional technical training with a forward-leaning approach to agentic coding, rapid ... Quantifind is a data science technology company whose AI platform uncovers signals of risk across ...

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All JobsAi Data Training Jobs

Ai Data Training information

What are the key skills and qualifications needed to thrive as an AI data trainer, and why are they important?

To thrive as an AI Data Trainer, you need a solid understanding of data annotation, machine learning fundamentals, and attention to detail, often backed by experience in data science or a related field. Familiarity with data labeling tools, annotation platforms, and version control systems is typically required. Strong analytical thinking, communication skills, and the ability to follow complex guidelines set top performers apart in this role. These skills ensure that high-quality, accurate datasets are produced to effectively train and improve AI models.

What is the difference between Ai Data Training vs Data Analyst?

AspectAi Data TrainingData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and other industries
Employer & Industry UsagePrimarily in AI development and machine learning projectsAcross various sectors analyzing data to inform decisions

Ai Data Training involves preparing and labeling data for AI models, focusing on machine learning algorithms. Data Analysts interpret data to generate insights for business decisions. While both roles work with data, Ai Data Training is more technical and model-focused, whereas Data Analysts focus on analysis and reporting.

What is AI data training?

AI data training refers to the process of teaching artificial intelligence systems, such as machine learning models, to recognize patterns and make decisions by feeding them large amounts of labeled data. This involves collecting, annotating, and preprocessing data so that the AI can learn from examples and improve its performance over time. Data trainers play a crucial role in ensuring that the data used is accurate, diverse, and relevant to the AI's intended tasks. Effective AI data training helps models become more accurate, reliable, and capable of handling real-world scenarios.

What are some common challenges faced in AI data training roles, and how can they be effectively managed?

Professionals in AI Data Training often encounter challenges such as ensuring data accuracy, managing large and potentially unstructured datasets, and maintaining consistency in labeling. These challenges can be managed through rigorous quality control checks, adopting clear annotation guidelines, and utilizing collaborative tools that streamline the review process. Being detail-oriented and communicating effectively with data scientists and engineers also helps in resolving ambiguities and improving overall data quality.
More about Ai Data Training jobs
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What job categories do people searching Ai Data Training jobs look for? The top searched job categories for Ai Data Training jobs are:
Ai Data Training jobs near you
Infographic showing various Ai Data Training job openings in the United States as of August 2026, with employment types broken down into 6% Internship, 66% Full Time, 22% Part Time, and 6% Contract. Highlights an 61% In-person, and 39% Remote job distribution.

AI Data Engineer

Schonfeld

New York, NY • On-site

$125K - $150K/yr

Full-time

Re-posted 2 days ago

Job description

About the Role
Schonfeld Strategic Advisors is seeking an experienced AI Data Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines that power SchonAI, our firm's internal AI platform. You will work at the intersection of data engineering and AI, ensuring that high-quality, timely, and relevant data flows seamlessly to our AI systems to support investment professionals across the firm.
Key Responsibilities
Data Pipeline Development
  • Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data to SchonAI using Prefect.
  • Develop ETL/ELT processes for diverse data sources including market data, research documents, internal databases, and third-party APIs.
  • Implement real-time and batch data processing workflows to meet varying latency requirements.
  • Ensure data quality, consistency, and integrity across all pipelines.

AI Data Infrastructure
  • Build and maintain data infrastructure optimized for AI/ML workloads, including vector databases and semantic search systems.
  • Design data schemas and storage solutions that support efficient retrieval and processing for LLM applications.
  • Implement data versioning, lineage tracking, and observability for AI training and inference pipelines.
  • Optimize data delivery for low-latency AI interactions and high-throughput batch processing.

Integration & Collaboration
  • Partner with AI engineers, software developers, and data scientists to understand data requirements.
  • Integrate with existing firm systems including risk platforms, trading systems, portfolio management tools, and research databases.
  • Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.
  • Work closely with business stakeholders to prioritize data sources and pipeline enhancements.

Data Governance & Security
  • Implement appropriate data access controls, encryption, and compliance measures.
  • Ensure adherence to data governance policies and regulatory requirements.
  • Monitor and maintain data pipeline performance, reliability, and cost efficiency.
  • Document data flows, transformations, and dependencies.

Required Qualifications
Technical Skills
  • Programming: Strong proficiency in Python; experience with SQL and at least one other language (e.g. Java, Scala, Go, Rust)
  • Data Engineering: 5+ years of experience building production data pipelines using tools like Apache Airflow, Prefect, Dagster, or similar
  • Big Data Technologies: Hands-on experience with distributed computing frameworks (Spark, Flink) and modern data platforms
  • Cloud Platforms: Proficiency with AWS services (S3, Kubernetes) or equivalent GCP services
  • Databases: Experience with both SQL (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB, Elasticsearch)
  • AI/ML Data: Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines

Preferred Experience
  • Experience building data pipelines for LLM applications or RAG (Retrieval Augmented Generation) systems
  • Familiarity with financial data sources (market data, fundamental data, alternative data)
  • Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
  • Experience of Analytics/Warehouse/OLAP DB (BigQ, SingleStore, RedShift, ClickHouse)
  • Experience with containerization (Docker) and orchestration (Kubernetes)
  • Understanding of MLOps practices and tools
  • Experience with data quality frameworks (Great Expectations, Deequ)

Professional Skills
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field
  • Strong problem-solving skills and attention to detail
  • Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
  • Experience working in fast-paced, collaborative environments
  • Self-motivated with ability to manage multiple priorities

Who we areSchonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.
Our CultureAt Schonfeld, we'll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas-at all levels-to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm's walls.
The base pay for this role is expected to be between $225k and $275k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.
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