ML Engineer — ASR

Kiefer

5d

About The Position

KIEFER is building Greece’s integrated AI ecosystem, spanning renewable energy infrastructure, AI systems, robotics, and enterprise applications. Founded in 2014, the company has delivered more than 600MW of energy projects and is developing sovereign AI infrastructure, enterprise AI products, and physical AI systems for Greece and Southeast Europe.

The ML Engineer will improve automatic speech recognition (ASR) for Sophea Meet, working with real meeting audio and owning the improvement cycle from data and model experiments through evaluation and production performance. The initial language focus is English. Additional languages, beginning with Greek, will be prioritized with Product according to usage and product needs.

The role involves training, adapting, and evaluating speech recognition models; building representative benchmarks and regression tests; preparing speech datasets and investigating challenging audio; using error analysis to guide improvements; optimizing inference; and deploying and monitoring model versions in collaboration with Engineering and Product.

The position offers a competitive compensation package aligned with talent benchmarks, hands-on impact shaping Kiefer Tech products, an AI-native environment, and an engineering-first culture with high autonomy and low bureaucracy.

Requirements

• At least 3 years of relevant ML or research engineering experience, with clear technical ownership and measurable results.
• Strong hands-on ASR or speech ML experience, including having shipped or materially improved a speech recognition system.
• Experience training, fine-tuning, or adapting deep learning models using real-world audio data.
• Strong evaluation skills, including WER/CER, benchmark design, error analysis, and regression testing.
• Strong Python skills and hands-on experience with PyTorch, JAX, TensorFlow, or a similar framework.
• Solid software engineering skills.
• Experience deploying, monitoring, and maintaining production ML systems.

Nice To Haves

• Multilingual ASR, accent robustness, domain adaptation, or diarization experience.
• Streaming speech recognition and low-latency inference experience.
• MLOps, evaluation, or data pipelines for speech systems.
• Experience with meeting transcription, voice agents, or enterprise speech products.

Responsibilities

• Train, fine-tune, adapt, and evaluate speech recognition models based on measured product needs.
• Build representative benchmarks and regression tests for real meeting audio.
• Prepare speech datasets and investigate difficult cases, including noise, overlapping speakers, long sessions, and specialized terminology.
• Use error analysis to determine which model, data, or pipeline changes will improve transcription quality.
• Improve inference across accuracy, latency, throughput, reliability, and cost.
• Deploy and monitor model versions with Engineering.
• Work with Product to set quality goals and prioritize improvements.

Benefits

• Competitive compensation package aligned with talent benchmarks.
• Hands-on work shaping AI capabilities for Kiefer Tech’s products and real-world applications.
• AI-native environment with challenges across model development, evaluation, and production AI systems.
• Engineering-first culture with high autonomy, low bureaucracy, and space to shape meaningful AI products.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed