[Remote] AI ML Engineer (7+ Years)
Note: The job is a remote job and is open to candidates in USA. InApp is seeking a Senior Python Developer who excels at building scalable, AI-integrated systems using modern tools and frameworks. This role combines backend expertise, cloud-native architecture, and hands-on AI integration to deliver intelligent, high-performance solutions.
Responsibilities
ā¢ Integrate APIs from multiple AI platforms (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) into scalable backend systems
ā¢ Build multi-model orchestration layers balancing cost, latency, and accuracy
ā¢ Fine-tune prompts, manage context windows, and implement RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases
ā¢ Optimize token usage, caching, and filtering strategies to enhance system efficiency and user experience
ā¢ Design and implement AI-enabled workflows seamlessly integrated with web, mobile, or enterprise ecosystems
ā¢ Develop Python-based backends and APIs using frameworks like FastAPI, Flask, or Django
ā¢ Build and deploy microservices and cloud-native services leveraging Docker, Kubernetes, and serverless architectures
ā¢ Collaborate with frontend, DevOps, and product teams to ensure smooth feature delivery and deployment
ā¢ Monitor and evaluate AI responses through metrics, evaluation frameworks, or RLHF-inspired feedback loops
ā¢ Implement AI guardrails for responsible usage including bias detection, toxicity filtering, and compliance enforcement
ā¢ Debug and resolve performance or reliability issues in AI-powered production systems
ā¢ Stay up to date with the evolving AI model landscape, exploring new models, APIs, and orchestration frameworks
ā¢ Experiment with multi-modal AI (vision, text, speech) for applicability in client scenarios
ā¢ Work closely with cross-functional teams to translate business goals into intelligent, automated features
Skills
ā¢ Expert in Python backend development with hands-on experience integrating AI models, building cloud-native microservices, and using AI-assisted coding tools for faster, smarter development
ā¢ Proven hands-on experience integrating LLM APIs (OpenAI, Claude, Gemini, Llama, etc.)
ā¢ Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.) as essential qualification
ā¢ Practical knowledge of LangChain, LlamaIndex, Codium or similar frameworks for AI workflow orchestration
ā¢ Understanding of prompt engineering, embeddings, vector databases (Pinecone, Weaviate, FAISS, pgvector), and RAG pipelines
ā¢ Strong background in cloud platforms (AWS, GCP, Azure), containerization, and orchestration
ā¢ Deep understanding of REST/GraphQL APIs, async programming, task queues, and caching mechanisms
ā¢ Familiarity with SQL/NoSQL databases (PostgreSQL, MongoDB, Redis)
ā¢ Experience using AI-assisted tools such as GitHub Copilot, ChatGPT API, AutoGen, or OpenDevin for coding and testing automation
ā¢ Exposure to CI/CD pipelines and Infrastructure as Code (Terraform, Pulumi)
ā¢ Knowledge of data preprocessing, NLP/NLU, and model evaluation techniques
ā¢ Data Engineering & Processing, Data pipeline development, ETL/ELT processes, Batch processing and stream processing frameworks, Large-scale data handling with pandas, NumPy, Dask
ā¢ Hands-on with multi-modal AI (vision, text-to-speech, speech-to-text)
ā¢ Experience with MLOps practices including CI/CD for AI pipelines, model monitoring, and drift detection
ā¢ Background in fine-tuning, reinforcement learning, or custom model training
ā¢ Familiarity with enterprise security standards (GDPR, HIPAA, SOC2)
ā¢ Contributions to open-source or personal AI-assisted coding initiatives
Company Overview
ā¢ Since 2000, InApp has been delivering full-cycle software development services to customers worldwide. It was founded in 2000, and is headquartered in Palo Alto, California, USA, with a workforce of 201-500 employees. Its website is http://www.inapp.com.
Company H1B Sponsorship
ā¢ InApp has a track record of offering H1B sponsorships, with 1 in 2025, 1 in 2024, 3 in 2023, 1 in 2022, 5 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now
Responsibilities
ā¢ Integrate APIs from multiple AI platforms (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) into scalable backend systems
ā¢ Build multi-model orchestration layers balancing cost, latency, and accuracy
ā¢ Fine-tune prompts, manage context windows, and implement RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases
ā¢ Optimize token usage, caching, and filtering strategies to enhance system efficiency and user experience
ā¢ Design and implement AI-enabled workflows seamlessly integrated with web, mobile, or enterprise ecosystems
ā¢ Develop Python-based backends and APIs using frameworks like FastAPI, Flask, or Django
ā¢ Build and deploy microservices and cloud-native services leveraging Docker, Kubernetes, and serverless architectures
ā¢ Collaborate with frontend, DevOps, and product teams to ensure smooth feature delivery and deployment
ā¢ Monitor and evaluate AI responses through metrics, evaluation frameworks, or RLHF-inspired feedback loops
ā¢ Implement AI guardrails for responsible usage including bias detection, toxicity filtering, and compliance enforcement
ā¢ Debug and resolve performance or reliability issues in AI-powered production systems
ā¢ Stay up to date with the evolving AI model landscape, exploring new models, APIs, and orchestration frameworks
ā¢ Experiment with multi-modal AI (vision, text, speech) for applicability in client scenarios
ā¢ Work closely with cross-functional teams to translate business goals into intelligent, automated features
Skills
ā¢ Expert in Python backend development with hands-on experience integrating AI models, building cloud-native microservices, and using AI-assisted coding tools for faster, smarter development
ā¢ Proven hands-on experience integrating LLM APIs (OpenAI, Claude, Gemini, Llama, etc.)
ā¢ Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.) as essential qualification
ā¢ Practical knowledge of LangChain, LlamaIndex, Codium or similar frameworks for AI workflow orchestration
ā¢ Understanding of prompt engineering, embeddings, vector databases (Pinecone, Weaviate, FAISS, pgvector), and RAG pipelines
ā¢ Strong background in cloud platforms (AWS, GCP, Azure), containerization, and orchestration
ā¢ Deep understanding of REST/GraphQL APIs, async programming, task queues, and caching mechanisms
ā¢ Familiarity with SQL/NoSQL databases (PostgreSQL, MongoDB, Redis)
ā¢ Experience using AI-assisted tools such as GitHub Copilot, ChatGPT API, AutoGen, or OpenDevin for coding and testing automation
ā¢ Exposure to CI/CD pipelines and Infrastructure as Code (Terraform, Pulumi)
ā¢ Knowledge of data preprocessing, NLP/NLU, and model evaluation techniques
ā¢ Data Engineering & Processing, Data pipeline development, ETL/ELT processes, Batch processing and stream processing frameworks, Large-scale data handling with pandas, NumPy, Dask
ā¢ Hands-on with multi-modal AI (vision, text-to-speech, speech-to-text)
ā¢ Experience with MLOps practices including CI/CD for AI pipelines, model monitoring, and drift detection
ā¢ Background in fine-tuning, reinforcement learning, or custom model training
ā¢ Familiarity with enterprise security standards (GDPR, HIPAA, SOC2)
ā¢ Contributions to open-source or personal AI-assisted coding initiatives
Company Overview
ā¢ Since 2000, InApp has been delivering full-cycle software development services to customers worldwide. It was founded in 2000, and is headquartered in Palo Alto, California, USA, with a workforce of 201-500 employees. Its website is http://www.inapp.com.
Company H1B Sponsorship
ā¢ InApp has a track record of offering H1B sponsorships, with 1 in 2025, 1 in 2024, 3 in 2023, 1 in 2022, 5 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Apply Now
Apply Now