PH - Machine Learning Engineer (GenAI Track)

Overview

Explore With Us

Are you looking to grow your career and make a meaningful impact? Interested to tackle new challenges? We’re looking for people like you!

The Proactive Hiring process is specifically designed for applicants who are seeking job opportunities at a later date. Applying for roles under Proactive Hiring means that you are applying for roles without immediate vacancies. However, we anticipate that we will need to hire for these roles in the next few months.

Here’s what you can expect when applying for a Proactive Hiring role :

Merit-based Evaluation : Your application will still undergo our standard skills- and values-based assessments.

Longer Lead Time : Turnaround time for processing Proactive Hiring applications may take longer than for Immediate Hiring applications, making it suitable for folks open to exploring opportunities!

Reserved Slot as a Priority Candidate : A successful application will result in a slot as one of our top candidates for the role. This is not yet a formal job offer, but expresses our intent to extend an offer to you once a vacancy becomes available.

First In Line for the Job : Once there is an active vacancy for the role, you will be one of the first people we contact and to whom we extend an official offer!

At Thinking Machines, we treat all our candidates with great care and fairness while ensuring we stay ahead of the curve to anticipate our clients’ needs.

Working at Thinking Machines

Thinking Machines is a technology consultancy building AI & data platforms to solve high-impact problems for our clients. Our vision is a future where data-driven decision-making is a norm and where AI is used to support humans in making excellent decisions. To do that, we create data cultures, one organization at a time.

We’re a company made up of intellectually curious, civic-minded, forever-learning individuals. We believe that great data science products are built with care for people and that the best way to drive inclusive innovation is to start with a diverse team.

Our field of work is incredibly dynamic, so we want to work with people who are committed to growing with us. We want to hire people who can demonstrate an ability to learn, then provide personalized coaching, growth opportunities, and a great working environment to get them to world-class.

Role Description

Thinking Machines is looking for a GenAI Engineer with a passion for Generative AI . You will be working on cutting-edge projects that leverage Large Language Models (LLMs) in building innovative conversational AI solutions. You'll tackle challenges like prompt engineering, model optimization, and ensuring seamless integration with existing systems. Your work will directly contribute to the creation of intelligent, responsive, and user-friendly AI solutions. If you're excited about the potential of GenAI and have the skills to bring it to life, we encourage you to apply!

As a GenAI Engineer, you'll be a key player in creating cutting-edge conversational AI solutions. You'll harness the power of Large Language Models (LLMs) to design, build, and deploy innovative solutions that redefine how people interact with technology.

This role goes beyond just model development. You'll be involved in the entire lifecycle of GenAI, from brainstorming and prototyping to deploying and monitoring production-ready systems. A core focus will be on building robust and reliable systems that can handle real-world demands. Think user-facing applications powered by our machine learning models, accessed through APIs for real-time predictions and constantly evolving through feedback mechanisms. Your expertise will ensure these systems are highly available and deliver a seamless user experience.

Key Responsibilities

LLM Integration : Integrate LLMs into solutions, ensuring seamless and natural language interactions.

Prompt Engineering : Develop and refine prompting strategies to elicit desired responses from LLMs and achieve specific conversational goals.

Fine-tuning and Optimization : Fine-tune pre-trained LLMs on specific tasks and datasets to improve performance and accuracy.

Data Processing : Process and prepare data for training and fine-tuning LLMs.

Model Evaluation : Evaluate the performance of LLMs and AI systems using appropriate metrics and methodologies.

MLOps : Contribute to the development and implementation of MLOps practices for GenAI systems, including model deployment, monitoring, and continuous improvement.

Collaboration : Collaborate effectively with cross-functional teams, including data scientists, software engineers, and product managers, to deliver high-quality GenAI solutions.

Research and Development : Stay abreast of the latest advancements in LLMs and GenAI research to identify and implement cutting-edge techniques.

Role Requirements

We’re looking for someone who has :

2+ years of experience in machine learning or software engineering work . Hands-on experience with LLMs and GenAI technologies is a plus.

Passion for GenAI : A strong interest in and enthusiasm for the field of GenAI and LLMs.

Coding Proficiency : Strong programming skills in Python and experience with relevant libraries (e.g., Transformers, LangChain).

Machine Learning Knowledge : Good foundations with machine learning principles and algorithms.

Cloud Computing Experience : Experience working with cloud platforms (e.g., Azure, AWS) and deploying machine learning models in cloud environments.

Problem-solving Skills : Excellent analytical and problem-solving skills.

Strong Communication Skills : Strong written and verbal communication skills to effectively collaborate and present technical ideas.

Initiative : Proactive and self-directed, with the ability to work independently and as part of a team.

Ideal candidates have

Experience with product development

Performed MLOps in a professional capacity

Relevant certifications (e.g. AWS Cloud Practitioner, or any Cloud ML Certificates)

Benefits and Perks

We offer the following compensation and benefits :

Competitive salary — the compensation amount is positively correlated with the difficulty of the job, relevant experience, fit, and skill factors.

Hybrid Set-Up — Hybrid-remote means employees are required to come in an average of two days a week for client engagements and internal in-person days intended for collaboration, socials, and strategic planning.

Individual professional development budget — an annual budget for conferences, training courses, books, and software is available to sharpen your skills and build new ones to help you grow in your role.

Full health benefits — generous health insurance package upon hiring, with options to include dependents.

Apprenticeship and yearly performance reviews with the leadership team to discuss career and personal goals, job progress and any questions and concerns.

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