Location: Fully Remote

Company: TensorOps

Employment Type: Full-Time

TensorOps is an AI Consulting Company helping top tier organizations design, build, and scale cutting edge AI and ML systems.

We work with ambitious teams to turn state of the art AI research into real-world products and infrastructure. Our engineers specialize in modern ML platforms, LLM architectures, and scalable data systems that move companies from experimentation to real impact.

We are now building our first dedicated marketing function and are looking for a founding team member who can define how TensorOps goes to market.

About the Role 

We are looking for a Founding Technical Marketing Lead to shape and refine TensorOps’ marketing engine from the ground up.

This role sits at the intersection of AI, engineering, and go-to-market strategy. You will be responsible for shaping how TensorOps communicates its technical expertise to the market, generating high-quality leads, and building a scalable marketing and sales pipeline.

This is not a traditional marketing role. We are looking for someone who understands complex technologies and knows how to translate them into compelling narratives that resonate with technical buyers.

You will own top-of-funnel growth, GTM strategy, and pipeline generation, while leading a small team of marketing and sales specialists. As a founding member of the marketing function, you will have the opportunity to define strategy, experiment quickly, and shape the long-term growth of the company.

Responsibilities

Go-To-Market (GTM) Strategy

• Define and execute TensorOps’ go-to-market strategy: Shape how TensorOps positions its services in the market and how we reach our target customers.
• Refine our Ideal Customer Profiles (ICPs): Identify the industries, companies, and technical buyers that benefit most from TensorOps’ expertise.
• Improve product–market positioning: Continuously refine how we communicate the value of our AI engineering services to technical audiences.

Pipeline & Lead Generation

• Generate premium top-of-funnel leads and SQLs: Design strategies that attract high-quality potential customers.
• Build and manage the marketing-to-sales pipeline: Ensure leads move efficiently from marketing into qualified opportunities.
• Optimize the funnel: Track performance and continuously improve how leads convert into business opportunities.

Technical Marketing & Content

• Develop technical marketing content: Create articles, insights, and thought leadership that resonate with engineering leaders and AI teams.
• Lead LinkedIn and digital marketing initiatives: Grow TensorOps’ presence and reach through targeted campaigns and strategic content.
• Translate complex technology into compelling narratives: Communicate technical topics in a way that is engaging and valuable for decision-makers.

Requirements

• At least 10 years of experience in Marketing or a related role
• Strong understanding of AI, machine learning, or data infrastructure
• Experience in B2B/B2D technical marketing
• Proven ability to generate pipeline and SQLs
• Experience contributing to go-to-market strategies
• Ability to translate complex technical topics into clear messaging
• Strong technical writing and storytelling skills
• Experience with LinkedIn marketing and thought leadership
• Comfortable working in a startup environment and building processes from scratch
• Data-driven mindset
• Experience working with technical audiences (engineers, data scientists, AI teams)

Nice to Have

• Experience organising industry events or conferences
• Experience running webinars or online technical events
• Experience building developer or AI communities
• Network: An existing network within the AI/ML community

If you’re ready to own GTM, lead a team, and drive real business impact in a highly technical environment, we’d love to meet you!

We are building a pipeline of talented Machine Learning Engineers for upcoming projects at TensorOps. While we may not have an immediate opening, we are continuously growing and would love to connect with strong candidates for future opportunities.

If you are passionate about ML systems, GenAI, and production-grade deployments, we’d love to hear from you.

About the role

We’re looking for Machine Learning Engineers who enjoy building practical, production-ready AI systems and collaborating on meaningful projects.

In this role, you will:

• Take ownership of key components within ML and GenAI projects, with support from senior team members when needed
  
  
• Contribute to architectural and technical decisions in a collaborative environment
  
  
• Build scalable ML systems that move from experimentation to real-world application
  
  
• Work with international clients to understand requirements and implement thoughtful technical solutions
  
  
• Support and mentor junior team members as you grow in your own leadership journey
  
  

You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning. 

Technical Expertise

We’re looking for engineers with strong hands-on experience across:

• Python: Writing clean, efficient, well-documented, production-quality code
  
  
• Machine Learning Frameworks: Designing, training, optimizing, and deploying models independently (e.g., PyTorch, TensorFlow, Scikit-learn)
  
  
• GenAI & LLM Systems: Building RAG pipelines, chatbot architectures, and applications using tools like LangChain
  
  
• MLOps & Production ML: Model versioning, monitoring, CI/CD for ML workflows
  
  
• Cloud Deployments: Deploying and scaling ML systems on AWS, GCP, or Azure
  
  
• Performance Optimization & Debugging: Diagnosing complex issues and improving system reliability and efficiency
  
  

Requirements 

• 2+ years of professional experience in Machine Learning, AI Engineering, or a related role
• Proven experience building and deploying ML models in production environments
• Experience working with stakeholders or clients is a plus
• Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
• Master’s degree in AI, Machine Learning, Computer Science, or a related field is a strong plus
• Equivalent practical experience building and deploying production ML systems will also be considered
  
  

What We Offer

• 100% Remote Work: Work from anywhere with flexibility and autonomy
• Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
• International Clients: Collaborate with global organizations and solve real-world challenges at scale
• Urban Sports Club Membership: Supporting your physical and mental wellbeing
• Monthly Bolt Credits: For rides
• Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate

Location: Remote

Duration: 2–4 months (project-based)

Type: Contract / Research Collaboration (Paid)

About the Project

We are looking for a Master’s or PhD student to work on fine-tuning large language models (LLMs) for domain-specific tasks. The goal is to take an existing pretrained model (e.g., Meta AI’s LLaMA-class models or similar) and specialize it for a narrow, high-value use case using efficient fine-tuning techniques.

This is a hands-on applied project designed for someone who wants real-world experience deploying and optimising LLM systems.

Help drive the next wave of applied AI by demonstrating how fine-tuned LLMs can unlock advanced, real-world use cases beyond general-purpose foundation models. Organizations that require domain-specific accuracy, self-hosted deployments, customisable workflows, or performance beyond out-of-the-box capabilities increasingly rely on fine-tuned models to meet those needs.

Through this project, you will contribute to building specialised AI systems that deliver improved accuracy, efficiency, and control compared to out-of-the-box models. You will also help bridge the gap between academic knowledge and real-world application by applying fine-tuning techniques to solve concrete business problems.

What You’ll Work On

• Fine-tuning pre-trained LLMs on small to medium datasets (500–20k examples)
• Implementing parameter-efficient fine-tuning (e.g., LoRA-style methods)
• Optimising training for cost and performance
• Running experiments on GPU cloud infrastructure
• Evaluating model performance and tradeoffs (specialisation vs generalisation)
• Deploying fine-tuned models for inference

Experience

• Strong Python skills
• Experience with deep learning frameworks: PyTorch (preferred) or TensorFlow
• Experience with Hugging Face Transformers or similar ecosystems
• Hands-on experience training or fine-tuning transformer models on GPUs (local or cloud-based)
• Previous experience using cloud platforms for model training or deployment (e.g., AWS, GCP, Azure, RunPod or similar GPU providers)
• Experience working with or fine-tuning open-weight LLM families (Gemma-3, Qwen-3.5, Llama 4, GPT-OSS, Mistral...)
• Hands-on experience with LoRA

Understanding of:

• Fine-tuning vs pretraining
• Overfitting and generalization
• Model evaluation
• Strong business awareness: ability to understand the context of the fine-tuning task and translate domain requirements into clear modeling objectives

What you bring

• MSc or PhD student in Computer Science, Machine Learning, AI, or related field
• Alternatively, 6 months of hands-on experience training and fine-tuning deep learning models
• Has worked on LLMs in research or industry
• Has fine-tuned at least one transformer model
• Comfortable working independently
• Interested in applied AI and real-world constraints (cost, latency, memory)

What You’ll Gain

• Real-world experience fine-tuning large models (30B–100B parameter class)
• Exposure to production constraints and deployment
• Opportunity to co-author technical writeups if applicable
• Strong applied portfolio project

What We Offer

• 100% Remote Work: Work from anywhere with flexibility and autonomy 
• Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
• International Clients: Collaborate with global organizations and solve real-world challenges at scale
• Urban Sports Club Membership: Supporting your physical and mental wellbeing
• Monthly Bolt Credits: For rides
• Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate