AI / ML Engineer

AI / ML Engineer

Department: Data Engineering

Employment Type: Permanent - Full Time

Location: Remote USA - In Tandem

Compensation: $125,000 - $140,000 / year

Description

At In Tandem, our tech solutions—which include OurFamilyWizard, Cozi, FamilyWall, and Custody Navigator—work in tandem with families to simplify daily life, fostering connection, organization, and peace of mind throughout key stages and milestones of family life. 
 
We believe technology can champion deeper connections within families, strengthen bonds, and improve communication. Our family of brands provides a range of solutions that streamline daily routines, offer resources and guidance during challenging times, and help families navigate those challenges with confidence, calm, and ease. 

As an AI/ML Engineer, you will lead the development, evaluation, and optimization of AI systems that enhance both user-facing features and internal tools. You’ll manage the full lifecycle of AI/ML models—spanning model selection, fine-tuning, deployment, and continuous improvement. Your work will span LLM-based applications, traditional ML models, and hybrid architectures—delivering intelligence and automation across our platforms. 

What you will accomplish:

Lead Model Development & Optimization 

• Own the end-to-end lifecycle of AI/ML models, from ideation to deployment and ongoing refinement 
• Create and curate datasets using real-world and synthetic data to train, validate, and evaluate models 
• Build hybrid systems that blend LLMs with traditional ML to balance performance, scalability, and interpretability 
• Fine-tune text & vision models and apply grounding techniques to improve factual accuracy and reduce hallucinations 

Evaluate and Iterate on LLM Applications 

• Implement collaborative evaluation frameworks for model performance across metrics such as accuracy, relevance, and output reliability 
• Add observability instrumentation (e.g., spans, traces, session tracking) to monitor real-world usage 
• Automate evaluation gates within CI/CD pipelines and lead the design of monitoring dashboards 
• Perform error analysis to identify failure modes and drive iterative improvements 
• Establish feedback loops using annotation strategies and sampling for continuous learning 

Drive Tooling and Product Integration 

• Partner with Product, Engineering, and Data teams to co-develop intelligent features for our co-parenting and family organization platforms 
• Design AI-powered tools to optimize internal workflows, such as content generation, communication, and customer support 
• Build robust APIs to expose ML services with a focus on reliability, scalability, and observability 

Who you are:

• Deeply technical and hands-on. You thrive on building and refining complex, intelligent systems from the ground up. 
• Theory meets practice. You understand cutting-edge research but apply it with pragmatism and user value in mind. 
• Collaborative evaluator. You lead with metrics, help teams align evaluation methods, and foster shared accountability. 
• Responsible innovator. You approach AI thoughtfully—with an emphasis on transparency, monitoring, and measurable user impact. 

What you bring:

• 5+ years in AI/ML engineering roles, with meaningful experience working with LLMs and generative AI (personal projects count!) 
• A proven track record of shipping ML systems into production environments 
• Strong background in model evaluation, error tracking, and metrics development (LLM-judge, structured evals, etc.) 
• Experience with AI-powered developer tools and code-generation workflows 
• Expertise in Python and ML libraries such as PyTorch, HuggingFace Transformers, vLLM 
• Knowledge of LLM fine-tuning techniques like LoRA, PEFT, RLHF, and dataset structuring strategies 
• Experience with orchestration tools (LangChain, Weights & Biases, MLflow) and model grounding  
• Applied experience with multi-modal models, vision model fine-tuning, or RAG systems 
• Comfort deploying models via APIs and managing endpoints for scalable inference 
• Working knowledge of AWS tools like Lambda, API Gateway, and SageMaker 
• Bonus: personal ML projects or contributions to open-source ML frameworks