AI Engineer - Data Scientist
The AI Engineer - Data Scientist role involves designing and building production-grade AI systems, focusing on advanced Generative AI and machine learning techniques. The position requires end-to-end ownership of AI solutions, including research, prototyping, deployment, and continuous improvement, collaborating closely with product and engineering teams to deliver scalable and measurable AI-driven business outcomes. This role is based in New York, NY, emphasizing strong software engineering practices and cross-team collaboration in a dynamic Confidential Client environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Software Development.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
- Translate ambiguous business problems into viable AI/ML solutions and delivery plans.
- Own AI systems end-to-end: research and prototype, implement, deploy, monitor, and iterate.
- Design and build LLM-based applications, retrieval-augmented generation (RAG) systems, and intelligent agents.
- Experiment with model architectures, prompting techniques, retrieval strategies, and agent workflows to improve quality and reliability.
- Create rigorous evaluation frameworks, metrics, and automated tests to measure AI performance and safety.
- Collaborate with product managers, software engineers, data engineers, and business stakeholders to deliver measurable outcomes.
- Drive best practices for production ML/AI (MLOps, CI/CD, monitoring, observability) and help scale capabilities across teams.
Required Qualifications
- Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, or a related quantitative/technical field.
- Minimum 2 years of professional experience building production-quality software, ML systems, or AI-driven applications using Python and/or C++.
- Strong foundation in probability, statistics, and applied machine learning (NLP, time-series analysis, or generative models).
- Solid software engineering fundamentals: modular design, APIs, testing, version control, and writing maintainable production code.
- Clear communicator who can explain complex technical concepts to both technical and non-technical stakeholders.
Nice to Have
- Graduate degree in a quantitative field (CS, Engineering, Math, Statistics, Physics).
- Hands-on experience building RAG systems, LLM applications, AI agents, or multimodal models.
- Exposure to reinforcement learning, recommendation systems, optimization methods, or advanced time-series modeling.
- Experience operating in ambiguous, fast-paced environments and quickly learning new technical domains.
Skills & Tools
- Python, C++
- LLMs (Generative AI), RAG, NLP
- PyTorch or TensorFlow
- Docker, Kubernetes, AWS/GCP/Azure
- SQL and data engineering tooling
- MLOps, CI/CD, monitoring and observability
Location & Schedule
This role is based in New York, NY. The Confidential Client maintains an in-office culture to support collaboration and career development; role-specific flexibility may be provided. Hours per week: 40. Shift: 1st shift.
Compensation
Base salary range: $107,300 - $193,200 per year (USD). Actual compensation will depend on experience, skills, and location. Benefits and total rewards details are provided by the Confidential Client.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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