Machine Learning Engineer

4 weeks ago

Manama, Bahrain Servable Full time

**About Us**

At Servable, we empower enterprises to adopt AI securely and efficiently with our all-in-one platform for deploying, fine-tuning, and serving large language models (LLMs). Our platform is designed to provide enterprise-grade security, scalability, and performance, making AI adoption seamless for industries like finance, telecom, and healthcare. We are looking for a **Machine Learning Engineer** to help build and optimize the model inference engine, fine-tuning pipelines, and other critical components of our platform.

**Role Overview**

As a Machine Learning Engineer, you will play a central role in building the infrastructure and systems that power model inference and fine-tuning on our platform. Your work will focus on integrating and optimizing LLM inference runtimes (e.g., vLLM, NVIDIA TensorRT) and ensuring compatibility with other model types in the future. You will also design and enhance our fine-tuning pipelines to make them robust, efficient, and scalable for enterprise use cases.

**Key Responsibilities**

**Inference Runtime Development**:

- Integrate and optimize LLM inference runtimes such as vLLM and NVIDIA TensorRT into our platform.
- Ensure compatibility with various model architectures, including future support for SLM, LVM, and LCM.
- Optimize inference pipelines for low-latency and high-throughput performance.

**Model Fine-Tuning Pipeline**:

- Build and improve fine-tuning pipelines to support parameter-efficient techniques like LoRA (Low-Rank Adaptation).
- Automate data preprocessing, training, and deployment workflows for fine-tuned models, and optimize on Synthetic Data Generation pipelines.
- Experiment with and implement advanced techniques for model customization and optimization.

**Infrastructure & Integration**:

- Collaborate with AI Infrastructure Engineers to deploy and scale model-serving systems across cloud and on-premise environments.
- Develop APIs and integration tools to enable seamless adoption of Servable’s inference and fine-tuning solutions.

**Collaboration & Innovation**:

- Work closely with Software Engineers and Product Managers to align ML features with customer needs.
- Research and implement cutting-edge techniques to improve inference performance and fine-tuning capabilities.
- Stay updated on advancements in AI/ML technologies and contribute to the evolution of our platform.

**What We’re Looking For**

**Must-Have**:

- 2+ years of experience working with AI/ML models, with a strong focus on NLP and LLMs.
- Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, and Keras.
- Experience with LLM inference optimization tools like vLLM, TensoRT-LLM, or Hugging Face Transformers.
- Strong understanding of distributed inference, model deployment, and optimization pipelines.
- Experience building and scaling ML pipelines, including preprocessing, training, and deployment.
- Strong understanding of fine-tuning techniques (QLoRa) and data preparation pipelines.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and distributed computing frameworks.
- Excellent problem-solving skills and ability to thrive in a fast-paced startup environment.

**Nice-to-Have**:

- Experience with QLoRA or similar parameter-efficient fine-tuning techniques.
- Hands-on experience with synthetic data generation.
- Knowledge of containerization and orchestration tools (Docker, Kubernetes).
- Familiarity with hybrid cloud/on-premise deployments for AI workloads.
- Background in AI infrastructure and distributed systems for high-performance computing.
- Understanding of enterprise security and compliance requirements for AI systems.

**Why Join Us?**
- **Cutting-Edge Work**: Tackle challenging AI problems and build impactful solutions for global enterprises.
- **Innovation**: Work on state-of-the-art AI technologies in a fast-growing, dynamic environment.
- **Ownership**: Play a critical role in shaping the technical foundation of our platform.
- **Collaboration**: Join a talented team dedicated to solving real-world problems with AI.
- **Competitive Compensation**: Competitive salary, equity options, and opportunities for professional development.

Ability to commute/relocate:

- Manama: Reliably commute or planning to relocate before starting work (preferred)

**Education**:

- Bachelor's (preferred)

**Experience**:

- programming: 1 year (preferred)

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