Job summary
Job post source
This job is directly from Tyndale Company, Inc.
Job overview
The Machine Learning Engineer at Tyndale Company, Inc. will drive AI and ML initiatives by owning the full lifecycle of ML models and generative AI applications, contributing to impactful innovations.
Responsibilities and impact
The role involves developing and deploying ML and generative AI models, building retrieval-augmented generation services, creating inference APIs, managing infrastructure as code, designing feature pipelines, setting evaluation metrics, and collaborating cross-functionally with data scientists, engineers, and stakeholders.
Compensation and benefits
The position offers competitive salary, comprehensive medical, dental, and vision insurance, paid parental leave, mental health support, 401(k) with matching, bonuses, generous PTO, hybrid work schedule, and career development programs including training and tuition reimbursement.
Experience and skills
Candidates must have a bachelor's degree in a related field, at least 4 years of ML engineering experience including 1 year with LLM or generative AI products, proficiency in Python, PyTorch or TensorFlow, SQL, LangChain/LlamaIndex, AWS production experience, Terraform, API design, and strong software engineering practices.
Career development
The company provides training, certification, tuition reimbursement, knowledge sharing, and clear paths for internal promotion to support career growth.
Work environment and culture
Tyndale Company fosters a family-owned, award-winning culture emphasizing collaboration, integrity, work-life balance with hybrid work options, and inclusive team engagement events.
Company information
Tyndale Company, Inc. is a 9-time Top Workplace winner in Pennsylvania, focusing on AI and machine learning innovations with a strong commitment to employee wellness and development.
Team overview
The candidate will join a growing AI organization collaborating closely with data scientists, data engineers, and business stakeholders to deliver AI-driven business impact.
Job location and travel
The position is hybrid with at least one onsite day per week at the corporate headquarters in Pipersville, PA, with remote work allowed for the remainder of the week; candidates must live within commuting distance.
Unique job features
This role uniquely involves working with cutting-edge generative AI tools like LangChain and LlamaIndex, managing ML infrastructure via Terraform and AWS, and delivering production-grade inference APIs with a focus on business impact.
Company overview
Tyndale Company, Inc. is a leading provider of flame-resistant (FR) clothing and managed apparel services, primarily serving industries like utilities, oil and gas, and manufacturing. The company generates revenue through the sale of FR garments and comprehensive uniform programs that include garment customization, laundry services, and compliance tracking. Founded in 1981, Tyndale has a rich history of innovation in safety apparel, emphasizing quality and customer service.
How to land this job
Position your resume to highlight your experience owning the full lifecycle of ML models and Generative AI applications, emphasizing rapid prototyping, containerization, and production deployment on AWS.
Focus on your proficiency with LangChain, LlamaIndex, vector databases like Pinecone or OpenSearch, and your hands-on work with infrastructure-as-code tools such as Terraform and AWS CDK.
Showcase your skills in designing and maintaining inference APIs using FastAPI or AWS Lambda, and your ability to collaborate cross-functionally with data scientists, engineers, and business stakeholders.
Apply through multiple platforms including Tyndale Company’s corporate career site and LinkedIn to maximize your application’s visibility and reach.
Connect with current Machine Learning Engineers or AI team members at Tyndale on LinkedIn; open conversations by referencing their recent AI projects or asking about their experience working on generative AI solutions at Tyndale.
Optimize your resume for ATS by incorporating keywords from the job description such as 'ML lifecycle', 'Generative AI', 'LangChain', 'Terraform', 'AWS SageMaker', 'FastAPI', and 'CI/CD', ensuring your resume passes automated screenings effectively.
Utilize Jennie Johnson’s Power Apply feature to automate tailored applications, identify multiple submission channels, and find relevant LinkedIn contacts to network with, freeing up your time to prepare for interviews and skill development.
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