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1mo ago

Financial Analytics Data Engineer

Daiichi Sankyo, Inc. Basking Ridge, NJ

Basking Ridge, NJ

1mo ago Closed

$127k - $191k/yr Full time Data Data Analysis Data Analytics

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Daiichi Sankyo, Inc. offers a Financial Analytics Data Engineer opportunity in Basking Ridge, NJ (onsite), where you will help turn analytical and product needs into scalable data and analytics products. The role emphasizes dependable data foundations through validation, monitoring, and quality controls, and includes ongoing evaluation of modern engineering approaches to support scalability, maintainability, and alignment with data governance and security standards.

What you’ll do

Design, develop, and maintain scalable data pipelines, including transformation logic and reusable datasets and data products for Financial Analytics use cases.
Translate analytical and product requirements into scalable technical implementations, supporting operationalization of analytical assets in productive environments.
Apply data validation, monitoring, and quality controls to ensure data foundations are reliable, trusted, and maintainable.
Collaborate with Financial Analytics Product Managers, Data Scientists, Global DX, and technical teams to align solutions with enterprise architecture, engineering standards, and delivery requirements.
Enable continuous improvement by evaluating modern data engineering approaches, improving scalability and maintainability, and ensuring compliance with data governance and security standards.

What you bring

Bachelor’s Degree required.
Master’s Degree preferred in data engineering, computer science, software engineering, information systems, data science, mathematics, finance, or a related field.
5+ years of data engineering, analytics engineering, software engineering, data management, or related fields, preferably supporting analytics or AI use cases in the finance domain.
Experience building and maintaining scalable data pipelines and analytical data solutions.
Experience with structured and semi-structured data environments and data transformation concepts.
Proven ability to work in cross-functional delivery environments and collaborate across technical teams.
Understanding of cloud-based data platforms, data architectures, and modern engineering practice preferred.
Experience in industries such as pharmaceuticals and chemicals preferred.

Compensation

Salary Range: USD$127,280.00 - USD$190,920.00 per year.

Benefits: Download Our Benefits Summary PDF.

Travel

Travel requirements: of the time. Limited.

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1mo ago

Data & AI Engineer

RevStar Virginia 🇺🇸 Remote

Virginia

1mo ago Closed

Full time Amazon Athena Amazon Web Services Artificial Intelligence

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

RevStar is hiring an experienced Data & AI Engineer for remote work in Virginia to build production-ready AI/ML solutions on AWS.

Responsibilities

Design, build, and deploy LLM-based APIs using Amazon Bedrock with models including Claude, Titan, Nova, and Cohere
Implement retrieval-augmented generation (RAG) pipelines using OpenSearch + S3
Build data pipelines for curated and raw data layers using AWS Glue, Athena, and Lake Formation
Support real-time reporting and AI usage dashboards via Amazon QuickSight
Design serverless workflows with AWS Lambda and manage prompt metadata using DynamoDB
Implement prompt orchestration strategies, including fallback handling, versioning, and safety guardrails
Collaborate with product managers, architects, and DevOps to align AI/ML delivery with customer and project goals
Document solutions clearly and support onboarding for handoff to client teams
Keep up with AWS advances in GenAI, MLOps, and scalable data platforms

Requirements

Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or a related field
5+ years designing, building, and deploying cloud-based ML or GenAI systems
Deep, hands-on experience with AWS AI/ML services including Amazon Bedrock, AgentCore, SageMaker, Lambda, S3, DynamoDB, Glue, Athena, Lake Formation, OpenSearch, and QuickSight
Strong Python skills for data manipulation, API development, and automation
Experience with RAG, prompt orchestration, or LLMOps workflows (preferred)
Familiarity with CI/CD, Infrastructure-as-Code (IaC), and Git-based workflows
Excellent communication skills, including the ability to explain AI system design and tradeoffs to technical and business stakeholders in a client-facing professional services environment

Technologies

Amazon Bedrock (Claude, Titan, Nova, Cohere)
OpenSearch, S3
AWS Glue, Athena, Lake Formation
Amazon QuickSight
AWS Lambda, DynamoDB
Amazon AgentCore, Amazon SageMaker
Python, CI/CD, Infrastructure-as-Code (IaC), Git
LLM Ops, MLOps

Benefits

Paid Time Off
Remote-First Working Environment
Comprehensive Health Coverage – Medical, Dental, Vision
401(k) Retirement Plan
Annual Learning & Development Stipend
Peer Mentorship & Coaching
Professional Growth Opportunities
Company Outings & Volunteer Opportunities
Collaborative, Innovative Culture

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1mo ago

Senior Applied AI Engineer

Curai Remote 🌍 Remote

Remote

1mo ago Closed

$175k - $200k/yr Full time Senior Artificial Intelligence Fine Tuning

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Curai is seeking a Senior Applied AI Engineer to design, build, and ship machine learning and LLM systems that influence how clinicians and patients engage with its healthcare platform. This role covers the full lifecycle, from problem framing and data exploration to training, evaluation, production inference, and measurement of real-world clinical and product impact.

Key Responsibilities

Lead the technical execution of complex AI initiatives, owning solution design and delivery within a product or technical domain, while collaborating with senior engineers on broader architectural direction.
Design, build, train, evaluate, and improve advanced machine learning and LLM-based systems for patient and provider-facing products, including use cases such as conversational AI, personalization, user understanding, clinical decision support, and chronic care management.
Own end-to-end problem work: scope with clinicians and product partners, create datasets and evaluations, iterate on modeling, and ship to production with appropriate monitoring and guardrails.
Develop robust evaluation frameworks, including offline benchmarks, human-in-the-loop review, and online experiments, to support confidence in model safety, accuracy, and ongoing improvement.
Build and enhance the team’s platform to accelerate delivery, including data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers.
Partner across clinicians, product, and engineering to translate medical and operational requirements into ML work and deliver measurable improvements to patient and clinician experience.
Provide technical direction for your area, mentor other engineers, and strengthen engineering and scientific rigor, with leadership scope that increases with seniority.
Stay current with the literature and the fast-moving AI ecosystem, and bring forward the most relevant ideas for patients and the team.

Required Qualifications

Bachelor’s degree in Computer Science, Software Engineering, Math, or a related technical degree.
3+ years of hands-on engineering experience, including 1+ years building and deploying machine learning systems with generative AI (LLMs), and a clear track record of impact.
Strong software engineering fundamentals, with the ability to ship reliable, well-tested Python (or comparable language) code in production.
Practical knowledge of modern LLM methods, including prompting, retrieval-augmented generation, fine-tuning, and evaluation, plus awareness of their trade-offs.
Ability to work with messy, real-world data and design evaluations that determine whether a system is actually working.
Strong written and verbal communication skills, including cross-collaboration with clinicians, product managers, and engineers.
A bias toward action and ownership, including the ability to take an ambiguous problem to a result and bring others along.
Motivation to align work with improved health outcomes for real patients.

Technologies

Python
LLMs
Retrieval-augmented generation
Prompting
Fine-tuning
Evaluation

Preferred Qualifications

Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain.
Experience with clinical NLP, medical knowledge representation, or working with electronic health record data.
Experience building agentic systems and tool-using LLMs in production.
Experience scaling ML infrastructure, including training pipelines, distributed inference, and evaluation platforms, for a small, fast-moving team.
Track record of technical leadership, such as setting direction across teams, mentoring engineers, or publishing influential work.

Benefits

High-ownership work on meaningful problems with a tight feedback loop from real clinicians and patients.
A small, senior team where work shows up in the product quickly.
Competitive compensation, meaningful equity, and comprehensive benefits.
Remote-first, flexible work environment across the U.S.
Comprehensive medical, dental, and vision coverage.
Flexible spending plans.
Generous and flexible Paid Time Off (PTO), floating holidays, and parental leave.
401k plan with employer matching.
100% remote, work from home.

Compensation

USD 175,000 - 200,000 per year. Actual base salary will depend on qualifications and years of relevant experience.

Location

Remote (remote), across the U.S.

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1mo ago

Embedded AI Engineer

Gigapower Dallas, TX 🇺🇸 Remote

Dallas, TX

1mo ago Closed

Full time Agentic Ai Ai Engineer Artificial Intelligence

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Gigapower is building AI capabilities that work alongside engineering teams, turning technical workflows into opportunities for automation and measurable productivity gains. As the dedicated Embedded AI Engineer, you will identify, develop, and deploy AI-powered solutions that support engineering operations across permit design, HLD/LLD, network planning, and day-to-day engineering processes.

Based in Dallas, TX (remote), this role partners closely with engineering, design, and permitting stakeholders to deliver practical tools such as RAG applications, intelligent agents, copilots, and internal engineering automations. You will also help drive adoption by coaching teams on AI tool usage and measuring real-world impact.

What you’ll do

Partner with Engineering, Design, and Permitting teams to understand workflows, challenges, and opportunities for AI-driven improvement.
Identify, prioritize, and deliver AI solutions that improve engineering productivity, design quality, permitting efficiency, and project execution.
Build and deploy AI-powered automations, retrieval-augmented generation (RAG) applications, intelligent agents, copilots, and internal engineering tools.
Develop solutions that streamline permit package creation, engineering documentation, design reviews, and standards compliance.
Create AI-enabled capabilities that assist with HLD and LLD development, engineering analysis, and network planning activities.
Collaborate with Data Engineering and AI teams on enterprise-scale solutions involving shared platforms, analytics, and operational data.
Coach engineering stakeholders on effective use of AI tools including Microsoft Copilot, Claude, and ChatGPT.
Measure solution adoption, quality, and business impact, continuously improving capabilities based on stakeholder feedback.
Partner with engineering leadership to identify scalable AI opportunities across network design and deployment activities.
Use AI-powered tools to improve personal productivity and accelerate solution development.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related discipline (or equivalent practical experience).
1 to 3 years of experience developing software, analytics, automation, or AI-based solutions.
Hands-on experience building applications utilizing Large Language Models (LLMs), including prompting, retrieval-augmented generation (RAG), AI agents, automation workflows, or tool integrations.
Strong proficiency in Python.
Experience developing solutions from concept through deployment and user adoption.
Working knowledge of SQL and experience working with structured datasets.
Strong communication skills, including the ability to explain technical concepts to non-technical audiences.
Demonstrated ability to operate independently and manage competing priorities in a fast-paced environment.
Strong problem-solving, analytical, and critical-thinking skills.
Enthusiasm for learning new technologies and understanding complex business operations.

Technologies

Python, SQL
Large Language Models (LLMs)
Retrieval-augmented generation (RAG)
AI agents
Microsoft Copilot, Claude, ChatGPT
Azure, Snowflake
Cloud-based analytics platforms, engineering systems

Preferred qualifications

Experience in fiber engineering, telecommunications engineering, network design, permitting, outside plant (OSP), or broadband infrastructure.
Familiarity with high-level design (HLD), low-level design (LLD), fiber routing, network planning, or engineering documentation processes.
Working knowledge of SQL and experience with structured, geospatial, or GIS-based datasets.
Experience with Azure, Snowflake, cloud-based analytics platforms, or engineering systems.
Experience supporting change management, technology adoption, enablement, or training initiatives.

Key competencies

Engineering Process Optimization: Identifies opportunities to improve engineering efficiency, quality, and consistency through technology.
AI Solution Development: Designs and delivers practical AI-powered solutions that create measurable business value.
Technical Partnership: Builds trusted relationships with engineers, designers, and technical stakeholders to solve complex operational challenges.
Problem Solving & Analysis: Applies data-driven thinking and technical expertise to address engineering and network design challenges.
Innovation & Automation: Continuously seeks opportunities to eliminate manual work and improve productivity through automation.
Communication & Influence: Clearly explains technical concepts, gains stakeholder buy-in, and drives adoption of new capabilities.
Learning Agility: Quickly learns new technologies, engineering processes, and business domains to maximize impact.

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1mo ago

Senior AI Engineer

Ultimus Fund Solutions Remote 🌍 Remote

Remote

1mo ago Closed

Full time Senior Artificial Intelligence Cloud Platform

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Ultimus Fund Solutions is seeking a Senior AI Engineer to take ownership of the full technical lifecycle for enterprise AI models, from data pipeline architecture through deployment and monitoring. This role is built for a hands-on engineering leader who can operationalize models in real production environments, partner with AI teams, and help translate operational needs into technical architecture.

Working remotely, you will partner with AI Data Scientists and AI Developers to ensure models are implemented with reliable data governance and delivered against measurable technical outcomes. You will also drive improvements that support system scalability and reduced latency, while establishing MLOps standards that track performance and reliability.

Responsibilities

Architect and scale machine learning pipelines that support automated workflows across Fund Accounting, Transfer Agency, and Onboarding
Oversee the development and deployment of robust AI infrastructure using enterprise data lakes and cloud platforms
Lead technical initiatives to integrate AI capabilities into legacy systems and financial platforms
Establish MLOps best practices and technical KPIs tied to system uptime, model latency, and infrastructure efficiency
Mentor junior engineering staff and advise the Managing Director on technical priorities and AI governance

Requirements

7+ years of experience across software engineering, data engineering, or machine learning operations
Proven ability to architect scalable data pipelines and deliver measurable technical outcomes
Deep expertise in Python and SQL, plus experience with enterprise cloud data platforms
Ability to work with business operations to translate operational needs into technical architecture
Experience in financial services or fund administration is preferred (not required)
Strong technical leadership and mentoring skills
An operator mindset focused on execution and reliable technical outcomes

Technologies

Python
SQL
Enterprise data lakes
Cloud platforms

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1mo ago

Embedded AI Engineer - Finance

Gigapower Dallas, TX 🇺🇸 Remote

Dallas, TX

1mo ago Closed

Full time Agentic Ai Ai Engineer Analytics

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Embedded AI Engineer to serve as the dedicated AI partner for the Finance organization, building and deploying AI-powered solutions that improve planning, forecasting, reporting, and decision-making.

Responsibilities

Work with Finance teams to understand budgeting, forecasting, capital planning, reporting, and approval workflows
Spot and rank use cases where AI can improve financial analysis, operational efficiency, and decision-making
Design and deploy AI-powered automations, RAG applications, agents, copilots, and internal productivity tools
Streamline financial reporting, forecasting, cost analysis, and capital approval processes through solution development
Collaborate with Data Engineering and AI teams on enterprise-scale platforms and shared data initiatives
Build tools that increase visibility into spend, capital deployment, project economics, and business performance
Coach stakeholders on using Microsoft Copilot, Claude, ChatGPT, and other AI technologies effectively
Track adoption, quality, and business outcomes to iterate and continuously improve delivered solutions
Reduce manual effort using workflow automation and intelligent reporting capabilities
Identify scalable AI opportunities that can be rolled out across multiple business functions

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, Finance, or a related discipline, or equivalent experience
1 to 3 years of experience building software, analytics, automation, data, or AI-based solutions
Hands-on experience with LLMs, prompt engineering, RAG, AI agents, or automation workflows
Strong proficiency in Python
Working knowledge of SQL and experience working with structured datasets
Capability to take solutions from concept through deployment and user adoption
Strong communication and stakeholder management skills
Self-starter mindset with comfort operating in fast-paced and ambiguous environments
Strong analytical, problem-solving, and critical-thinking skills
Interest in learning complex financial and business processes

Technologies

Python
SQL
LLMs
RAG
Microsoft Copilot
Claude
ChatGPT
AI agents

Preferred Qualifications

Experience in corporate finance, FP&A, capital planning, financial analytics, or infrastructure cost estimation
Experience supporting telecommunications, construction, utilities, infrastructure, or capital-intensive industries
Experience with Azure, Snowflake, cloud analytics platforms, or modern data environments
Experience with change management, user enablement, training, or technology adoption initiatives

Key Competencies

Financial Process Optimization: Improve efficiency, accuracy, and scalability of finance operations using technology
AI Solution Development: Deliver AI-powered solutions tied to measurable business value
Business Partnership: Build trusted relationships with finance and operational stakeholders
Data-Driven Decision Making: Use data, analytics, and AI to provide actionable insights
Automation & Innovation: Identify opportunities to remove manual effort and increase productivity
Communication & Influence: Explain technical concepts clearly and drive adoption across stakeholder groups
Learning Agility: Quickly build expertise in financial processes, technologies, and business domains

Location: Dallas, TX (remote). Experience: 1+ years.

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1mo ago

Principal Data Scientist - AI Trainer

DataAnnotation Tampa, FL 🇺🇸 Remote

Tampa, FL

1mo ago Closed

$50 - $100/hr Contract Artificial Intelligence Data & Ai Data Analysis

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

DataAnnotation is hiring a Principal Data Scientist - AI Trainer to help train and evaluate AI models focused on quantitative reasoning. This fully remote contract role centers on assessing AI-generated work, building and benchmarking quantitative problem sets, and providing feedback that improves model performance. After completing an assessment, successful candidates can access paid projects on the platform.

The position supports a flexible, project-based workflow and pays hourly. Work can be done on your own computer, and projects may vary depending on the training and evaluation needs for quantitative reasoning tasks.

Responsibilities

Evaluate AI-generated quantitative outputs, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, checking for technical accuracy and real-world validity.
Design and solve quantitative problems used to train and benchmark AI systems across areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well-documented analytical code.
Deliver feedback that informs improvements for the next generation of AI models used for quantitative reasoning.

Requirements

3+ years of hands-on experience in a quantitative role or research environment (for example, data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a related field).
Some coding experience and the ability to write and review analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
Fluency in English (native or bilingual) with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a Master’s or PhD is a plus.
Relevant credentials are a plus, such as a strong Kaggle Competition ranking or AWS/GCP ML certifications (or equivalent demonstrated expertise).

Technologies

Contract Details and Location

Location: Tampa, FL (remote)
Job type: contract
Compensation: USD 50 to 100 per hour

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: select projects and work timing, using your own computer.
Competitive pay: projects are paid hourly at $50 to $100 USD per hour, with bonus rates available on some projects.
Impact: contribute to AI systems designed to reason about data and analytics.

Assessment and Payment

Payment is made via PayPal.
No money will be requested from you.
Once you sign up for an account, you’ll take a short assessment (used as an interview). If you pass, you’ll receive email confirmation and paid work will be available on the platform.

1mo ago Closed

Contract Data Analysis Data Analytics Database

1mo ago

Senior Machine Learning Engineer

Motion Recruitment Wilmington, MA

Wilmington, MA

1mo ago Closed

Full time Senior Artificial Intelligence Data Analysis

1mo ago

Machine Learning Engineer - AI Trainer

DataAnnotation Massachusetts 🇺🇸 Remote

Massachusetts

1mo ago Closed

$50 - $100/hr Contract Ai Ml Ai Model Training Ai Training

1mo ago

Machine Learning Engineer - AI Trainer

Phoenix, AZ

1mo ago Closed

$123k - $215k/yr Full time Senior Agentic Ai Agentic Ai Orchestration

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