Senior Machine Learning Engineer

Posted about 2 months agoViewed

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💎 Seniority level: Senior, 5+ years

📍 Location: Worldwide

🔍 Industry: Software Development

🏢 Company: Zencoder

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: PythonGitMachine LearningREST APICI/CDDevOpsSoftware Engineering

Requirements:

5+ years of experience in the ML/AI field.
Deep understanding of machine learning, including experience with some fields of classical ML (recommendation systems, regressions/classifications on tabular data, and time series or other areas of classical ML).
Deep understanding of modern NLP: different providers strengths and weaknesses, best OS models, SOTA ways to finetune, quantize and distill models.
Experience with fine-tuning using RLHF or DPO.
Ability to set up data collection pipelines.
Proficiency in Python.
Ability to explain complex AI concepts and architectures clearly.
Deep understanding and experience of enterprise software development processes, ability to formalize typical SDLC tasks with all nuances.
Strong analytical and problem-solving abilities, with a knack for troubleshooting and debugging complex issues.
Proven ability to work effectively in a collaborative team environment, with excellent communication skills and a commitment to delivering high-quality solutions on time.
Eagerness to learn and adapt to new technologies and methodologies, with a passion for continuous improvement and innovation.
Ability to work in dynamic, fast-changing environments or experience in start-ups.
Prior experience in creating developer tools loved by their users would be highly advantageous, especially for VS and JetBrains add-ins.
Experience with RAG and multi-agent pipelines is a plus.

Responsibilities:

Create embedded AI agents pipelines; design, train, and implement advanced AI models focusing on LLMs, LMMs, and RL.
Collaborate with the AI and SWE teams to conceptualize, design, and build a code-generation add-in that empowers developers to automate repetitive tasks and boost productivity.
Conduct thorough testing of developed solutions, identify and address any bugs or performance issues, and optimize code for efficiency and scalability.
Stay updated with the latest trends and advancements in full-stack development, DevOps practices, and AI technologies to drive innovation and maintain competitiveness.
Influence how software development will be done in the whole industry.

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