SLM Engineer
New York, New York, United States of America
Contract
3 days ago
$45 - $60 USD
Key skills
PythonAIMLGenerative AIGenAIAnthropicPyTorchHugging FaceAWSDockerECSEKSLambdaS3SageMakerBedrockCI/CD
About this role
RESPONSIBILITIES:
Kforce has a client in NYC that is seeking an SLM Engineer who will be designing, fine-tuning, and deploying small to mid-sized language models (SLMs) using AWS Bedrock. This role is centered on hands-on model customization, optimization, and production integration within an AWS-native environment.
Ideal Candidate Profile:
* Background: ML Engineer, AI Engineer, or Software Engineer focused on GenAI applications
* Strengths: Fine-tuning, Bedrock implementation, and production deployment
* Languages: Python required
* Environment: AWS-first, strong familiarity with Bedrock and cloud-native AI patterns
* Mindset: Builder focused on delivering usable, scalable AI solutions
What Success Looks Like:
* Successfully deploys Bedrock-powered models into production environments
* Fine-tunes and optimizes models for domain-specific accuracy and performance
* Improves response quality, latency, and cost efficiency over time
* Integrates AI capabilities seamlessly into real-world applications
Duties:
* Optimize models for latency, cost, and performance in real-world environments
* Run experiments and iterate based on measurable improvements
* Build and deploy APIs to serve models in production
* Integrate Bedrock-powered models into applications and enterprise systems
* Develop pipelines for training, evaluation, and deployment workflows
* Partner with application and data teams to embed AI into business processes
REQUIREMENTS:
* Strong hands-on experience with AWS Bedrock for building and deploying generative AI solutions
* Experience working with foundation models available through Bedrock (Anthropic, Meta, etc.)
* Ability to configure, customize, and optimize models within Bedrock for specific use cases
* Familiarity with broader AWS ecosystem: SageMaker, S3, Lambda, ECS/EKS
* Experience deploying scalable, production-ready AI services in AWS
* Practical experience working with language models and transformer-based architectures
* Experience adapting models for domain-specific use cases such as summarization, Q&A, or classification
* Strong understanding of how to evaluate and improve model outputs
* Familiarity with prompt engineering and instruction tuning techniques
* Hands-on experience with fine-tuning models using Python-based frameworks (Hugging Face, PyTorch, etc.)
* Experience with parameter-efficient fine-tuning techniques: LoRA, PEFT, adapters
* Ability to prepare and manage training datasets including cleaning and labeling
* Experience with ML lifecycle management: Model versioning, monitoring, retraining workflows
* Experience with CI/CD pipelines for ML and AI workloads
* Familiarity with containerization (Docker) and deployment in ECS/EKS
* Understanding of GPU and accelerated compute environments
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
Kforce has a client in NYC that is seeking an SLM Engineer who will be designing, fine-tuning, and deploying small to mid-sized language models (SLMs) using AWS Bedrock. This role is centered on hands-on model customization, optimization, and production integration within an AWS-native environment.
Ideal Candidate Profile:
* Background: ML Engineer, AI Engineer, or Software Engineer focused on GenAI applications
* Strengths: Fine-tuning, Bedrock implementation, and production deployment
* Languages: Python required
* Environment: AWS-first, strong familiarity with Bedrock and cloud-native AI patterns
* Mindset: Builder focused on delivering usable, scalable AI solutions
What Success Looks Like:
* Successfully deploys Bedrock-powered models into production environments
* Fine-tunes and optimizes models for domain-specific accuracy and performance
* Improves response quality, latency, and cost efficiency over time
* Integrates AI capabilities seamlessly into real-world applications
Duties:
* Optimize models for latency, cost, and performance in real-world environments
* Run experiments and iterate based on measurable improvements
* Build and deploy APIs to serve models in production
* Integrate Bedrock-powered models into applications and enterprise systems
* Develop pipelines for training, evaluation, and deployment workflows
* Partner with application and data teams to embed AI into business processes
REQUIREMENTS:
* Strong hands-on experience with AWS Bedrock for building and deploying generative AI solutions
* Experience working with foundation models available through Bedrock (Anthropic, Meta, etc.)
* Ability to configure, customize, and optimize models within Bedrock for specific use cases
* Familiarity with broader AWS ecosystem: SageMaker, S3, Lambda, ECS/EKS
* Experience deploying scalable, production-ready AI services in AWS
* Practical experience working with language models and transformer-based architectures
* Experience adapting models for domain-specific use cases such as summarization, Q&A, or classification
* Strong understanding of how to evaluate and improve model outputs
* Familiarity with prompt engineering and instruction tuning techniques
* Hands-on experience with fine-tuning models using Python-based frameworks (Hugging Face, PyTorch, etc.)
* Experience with parameter-efficient fine-tuning techniques: LoRA, PEFT, adapters
* Ability to prepare and manage training datasets including cleaning and labeling
* Experience with ML lifecycle management: Model versioning, monitoring, retraining workflows
* Experience with CI/CD pipelines for ML and AI workloads
* Familiarity with containerization (Docker) and deployment in ECS/EKS
* Understanding of GPU and accelerated compute environments
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.