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ML Engineer at Rivendell Technologies Inc · Remote only · 0 - 8 years · $0.5K - $8K / yr · Raised funding · Remote only · Posted 10 Jul 2024

Rivendell Technologies Inc's logo

ML Engineer

Michelle Inovejas's profile picture
Posted by Michelle Inovejas
0 - 8 yrs
$0.5K - $8K / yr
Remote only
Skills
skill iconMachine Learning (ML)

ML Engineer

HackerPulse is a new and growing company. We help software engineers showcase their skills using AI powered profiles. As a Machine Learning Engineer, you will have the opportunity to contribute to the development and implementation of advanced Machine Learning (ML) and Natural Language Processing (NLP) solutions. You will play a crucial role in taking the innovative work done by our research team and turning it into practical solutions for production deployment. By applying to this job you agree to receive communication from us.


*Make sure to fill out the link below*

To speed up the hiring process, kindly complete the following link: https://airtable.com/appcWHN5MIs3DJEj9/shriREagoEMhlfw84


Responsibilities:

  1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.
  2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.
  3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.
  4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.
  5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.
  6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.
  7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.
  8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.
  9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.
  10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.
  11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.
  12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.

Qualifications:

  1. Degree in Computer Science or related discipline or equivalent practical experience, with a strong emphasis on machine learning and natural language processing.
  2. Proven experience and in-depth knowledge of ML techniques, with a focus on implementing deep-learning approaches for NLP tasks in the context of productizing research goals.
  3. Ability to apply engineering best practices to make architectural and design decisions aligned with functionalities, user experience, performance, reliability, and scalability in the development of deployable ML services.
  4. Substantial experience in software development using Python, Java, and/or C or C++, with a particular emphasis on integrating machine learning models into production-ready software solutions.
  5. Demonstrated problem-solving skills, showcasing the ability to address complex situations effectively, especially in the context of improving models, data engineering, and deployment processes.
  6. Strong interpersonal and communication skills, essential for effective collaboration within cross-functional teams consisting of research, development, and frontend teams.
  7. Proven time management skills to handle dynamic and agile development situations, ensuring timely delivery of solutions in a fast-paced environment.
  8. Self-motivated contributor who frequently takes initiative to enhance the codebase and share best practices, contributing to the development of an open, transparent, and collaborative engineering culture.


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About Rivendell Technologies Inc

Founded :
2023
Type :
Services
Size :
20-100
Stage :
Raised funding

About

Rivendell New Age Gifts NZ offers a wide range of products including Crystals, Gemstone Jewellery, Greenstone, Copper Bracelets, Lamps, Incense, Oils, Tarot Cards, and Fairies. Customers can shop online for these unique items and enjoy free shipping on...
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● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.


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● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

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• Lang Chain , Lang Graph

• Spark

• Agentic AI Design

• ML Ops

• MCP (client and server)

• FastAPI

• Doc Factory

• RAG

• Golang

• LLMs – Gemini, Open AI

• NLP

• Dev Assistant - AI based code - generation

(Qwen or Claude or Copilot)

• CI/CD

• Good in oral and written communication,

collaboration and be a team player

Good to have skills 

• DevOps with K8

• Scripting

• Java

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LeadSquared
LeadSquared
Agency job
via by Vrishali Mishra
Bengaluru (Bangalore)
2 - 4 yrs
Best in industry
PyTorch
TensorFlow
Agentic AI

About the Role

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

 

About the Role

We are looking for a Senior AI/ML Backend Engineer to help build the core intelligence layer powering Lumen and Agent Studio. You will design and ship production-grade backend systems that integrate LLMs into real agentic workflows — taking actions, retrieving knowledge and generating insights inside a live CRM product used by real businesses. This is a hands-on, build-focused role with direct ownership of systems that ship to production.

What You’ll Do

  • Design, build and scale backend services in Python that power LLM-driven and agentic features within Lumen and Agent Studio.
  • Build and productionize agentic AI systems — including planning, tool use, orchestration, memory and multi-step task execution.
  • Integrate LLMs into core product workflows, focusing on reliability, latency, cost and correctness at production scale.
  • Build robust APIs and services that connect AI agents with CRM data, business logic and third-party systems.
  • Own evaluation, testing and monitoring for AI features to ensure they behave reliably in real-world, not just demo, conditions.
  • Collaborate closely with product, design and other engineers to take features from zero to one and iterate rapidly based on real usage and customer feedback.
  • Work directly with customers and customer-facing teams to understand real workflows, debug issues and translate feedback into product and engineering decisions.

What We’re Looking For

  • 2–4 years of professional backend engineering experience, with strong hands-on Python skills.
  • Design and build LLM-powered agentic systems using frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI to automate complex, multi-step workflows.
  • Should be hands-on with traditional Machine learning frameworks like Pytorch, Scikit-learn
  • Solid understanding of API design, backend architecture, databases and distributed systems fundamentals.
  • Familiarity with LLM orchestration concepts — prompting, tool/function calling, RAG, agent frameworks, evaluation and guardrails.
  • Comfort working in a fast-paced, ambiguous, zero-to-one environment where you’ll be defining as much as building.
  • Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

  • Experience with enterprise security, reliability or observability practices for AI systems.
  • Prior experience working on CRM, SaaS or other enterprise business software.
  • Exposure to voice AI or real-time systems.

 


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Shubham Vishwakarma

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