Remote Software engineering Jobs • NLP

We are looking for a Software Development Engineer II with 2–4 years of experience, including hands-on involvement in at least one AI/ML/NLP-based project. This role focuses on building intelligent internal systems that leverage AI to automate complex workflows and enhance internal efficiencies. You will be working at the intersection of backend engineering, machine learning, and platform design—crafting intelligent systems that support business operations at scale.

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineering Manager. Lead the design and implementation of complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. Lead and work in a collaborative team environment creating practical, efficient, and high-performance software that leverages Large Language Models and other ML models and techniques.

Infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Senior Machine Learning Engineer. Design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. Apply AI/ML concepts to difficult problems and develop scalable solutions, creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities.

Miratech seeks a CCAI BOT Developer to join our team remotely, focusing on developing and implementing advanced conversational AI solutions using the Google CCAI Bot framework, collaborating to build intelligent voice bots and chatbots that enhance customer interactions.

We are seeking a highly skilled GenAI Engineer to play a key role in advancing our AI-driven platform and client solutions. The ideal candidate has 4+ years of hands-on ML experience beyond academia, thrives in fast-paced environments, and enjoys solving complex technical challenges. A strong foundation in cloud-based ML solutions, AI model deployment, and optimization techniques is essential.

You'll collaborate with different functions and be hands-on across the full stack: from data and modeling to software systems and observability. You’ll grow quickly, owning meaningful pieces of the products with ultimate support from experienced engineers and scientists around you. Design, build and release AI products/features that solve real user problems. Design and implement streaming/batch data pipelines to support training and inference. Write production-ready code, and move it to production with the help of cloud services and CI/CD techniques.

Tech team is expanding rapidly to keep pace with the ambitious feature roadmap the company has set out. This role involves helping to define the roadmap and find the best technical solutions to help customers. Also, you will have time to run some experiments and bring new ideas to the table.

Blue Orange is seeking an experienced Machine Learning Engineer to address expanding opportunities with a deep passion for machine learning, AI tech and innovative data solutions. The candidate will play a crucial role in driving our machine-learning initiatives forward and will have excellent communication skills to collaborate with technical and non-technical stakeholders effectively.

The AI Engineering Leader has a pivotal role in our organization, responsible for guiding the team that develops enterprise-level solutions aimed at scaling and automating value-driven outcomes for our business. The leader will oversee all aspects of AI engineering, from conceptualization to deployment, ensuring the delivery of cutting-edge solutions that meet both business and technical requirements.

Design, build, evaluate, and ship ML solutions in Spotify’s personalization products and collaborate with cross functional teams to build new product features that advance the mission to connect artists and fans. Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users. Promote and role-model best practices of ML systems development throughout the organization and be part of an active group of machine learning practitioners.