Offer summary

Qualifications:

4+ years of ML engineering experience, Bachelor’s degree in Computer Science or related field, Proficiency in Python and ML libraries such as PyTorch and TensorFlow, Experience with building GenAI solutions and client-facing roles..

Key responsibilities:

Design and implement complex ML systems adhering to best practices

Lead client communications and manage project expectations

Analyze model errors and optimize models for performance and scalability

Provide mentorship to junior ML engineers and collaborate with cross-functional teams.

Job description

Years from now, history will look back at this moment as a landmark for the human race—the moment when generative artificial intelligence began to change everything. Luckily, you happen to be living through it. Now what?

If you’re one of those rare people driven to add their intellectual energy to the relentless momentum of technological advancement, consider Loka your optimal leverage point.

Loka, a globally distributed tech consultancy based in Silicon Valley, is seeking a Senior Machine Learning Engineer to join our growing team. In this position you will serve as the primary specialist in designing and implementing machine learning solutions across multiple projects. Your expertise in ML algorithms and ML, DL and Foundation Models will empower us to develop robust, scalable systems and improve them over time. Ultimately we expect you to not just fit in with our ML crew but to elevate it to new heights.

Our technical teams help clients launch innovations that fix the climate, defeat cancer, improve agricultural efficiencies, teach kids to read and more. We work with all kinds of companies, from Silicon Valley startups to major household brands, always guided by our fundamental belief that mission matters.

We count more than 100 certified specialists, technical experts and PhDs among our teammates—committed Lokals who contribute to their brilliance not only to serving our clients but to mentoring junior colleagues as well. We work entirely remotely, test new ideas with an in-house incubator called LokaLabs, observe local holidays and take every other Friday off (really). We’re as proud of our culture as we are of our projects. You will be too.

The Role

Take full responsibility for assigned tasks and projects, ensuring accountability for outcomes and results.
Understand business objectives and develop models that help achieve them, along with metrics to track progress.
Design and implement complex ML systems using classical machine learning, deep learning and foundation models, adhering to best practices.
Lead client communications by gathering requirements, managing expectations and communicating deliverables effectively.
Wrangle, explore and visualize data with a keen eye for issues requiring data cleaning, as well as differences in data distribution that may affect post-deployment performance.
Analyze model errors and design strategies to overcome them.
Deploy, maintain and upgrade ML models and pipelines.
Follow Loka’s career track for growth by demonstrating technical excellence, innovation, autonomy, ownership, communication and teamwork.
Drive architectural decisions and contribute to high-level planning and strategy.
Direct report to ML leads.
Stay updated with industry trends to incorporate cutting-edge techniques and tools into projects.
Write and maintain technical documentation.
Provide guidance and mentorship to junior ML engineers within the team.
Collaborate cross-functionally with other teams (Data Engineering, DevOps, Backend) to ensure seamless integration of ML solutions.
Continuously optimize models for performance, scalability and cost-effectiveness, especially within the AWS environment.

Required Hard Skills

4+ years of ML engineering experience
Bachelor’s degree in Computer Science or related
Experience with Python, ML libraries and AI/ML frameworks (PyTorch, HuggingFace, TensorFlow, etc.)
Experience building GenAI solutions using LLMs, including frameworks like LangChain and LlamaIndex, prompt engineering, fine-tuning and serving models, and implementing common patterns like RAG and NLQ
Client-facing experience
Familiarity with containerization and orchestration tools

Additional Requirements

Excellent English - Being a global team, we work entirely in English for meetings, customer calls and business communications
CV sent in English

Not Required but Nice to Have

Experience with MLOps, preferably in AWS (e.g: Sagemaker), as well as standards tools (e.g. MLFlow)
Experience in consultancy environments or startups, including working directly with clients, managing projects and adapting to different settings. - Plus

Required Soft Skills

Curiosity: Strive to learn and grow into different industries with a modern tech stack.
Autonomy and positivity: We’re a fully remote, globally distributed team.
Teamwork: Enjoy a collaborative approach.
Adaptability: Operate with a startup mindset and move at a startup pace.

Benefits